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Update with 362 new publications to Deeplearning.University Bibliography

This update to Deeplearning.University has 362 new Deep Learning papers (all from 2015) collected in the period since last update (January 27th, 2015) and until today.  See the 362 new papers below, and deeplearning.university for the entire updated bibliography (it has more than 1000 papers now, 1324 to be accurate).

As always if you want have suggestions to the bibliography (in particular: improved Bibtex-entries or additions), please do that as git pull-requests on the file: https://github.com/memkite/DeepLearningBibliography/blob/master/bibtex/deeplearninggpuwithkeywords2014.bib

https://github.com/memkite/DeepLearningBibliography

Best regards,

Amund Tveit 


Links to Deep Learning Subtopics

[2d] [3d] [acoustic] [acoustic model] [action recognition] [action selection] [activity detection] [adaptive] [ads] [adversarial nets] [advertising] [aircraft detection] [algorithm] [alzheimer’s] [applications] [approximate] [architecture] [articulatory synthesis] [autoencoder] [autonomous] [autonomously] [batch] [batch normalization] [batchwise] [bayes] [bayesian] [behavior model] [behavior models] [belief propagation networks] [big] [big data] [big-data] [biologically] [bird] [blstm] [boosted] [brain] [calibration] [cancer] [cascade] [cell] [challenges] [character recognition] [classification] [click-through] [cloud] [clustered] [clustering] [cnn] [coding scheme] [cognition] [cognitive] [collaborative filtering] [computer vision] [concept learning] [constrained] [content-based] [controller] [convnet] [convnets] [convolutional] [convolutional network] [convolutional neural network] [corpora] [ct] [data mining] [data-parallel] [dataset] [dcnn] [decision making] [deep belief nets] [deep belief network] [deep learning] [deep neural network] [deep sigmoid belief networks] [demodulation] [denoising] [depression] [depth-videos] [diacritization] [dictionary] [dictionary extraction] [discriminative] [disease] [distributed] [dnn] [dropout] [drug] [embedded] [emotion] [energy] [ensemble learning] [entities] [entity] [error correction] [estimation] [event] [face] [face recognition] [facial] [feature] [feature discovery] [feature encoding] [feature extraction] [feature selection] [features] [fine tuning] [fine-tuning] [fmri] [fpga] [fpga-based] [framework] [freehand] [fuzzy learning] [galaxy] [games] [gaussian] [generative] [genetic programming] [gesture] [gradient] [gradient-based] [graphical model] [graphics] [hand pose] [handwritten] [hardware] [hash] [hashing] [hearing aid] [hessian] [hierarchical] [hmax] [hmm-based] [hough transform] [human behavior] [human pose] [human-level] [hyperspectral] [image classification] [image recognition] [imagery] [imaging] [indexing] [information] [information retrieval] [information-theoretic] [invariant] [kernel] [kernels] [lasso] [latent structure] [learning to rank] [lfw] [linear model] [linear models] [logistic] [long short-term memory] [lstm] [machine translation] [medical] [medicine] [metric learning] [mimd] [missing] [mobile] [monte carlo] [motion] [mri] [multi-label] [multicore] [natural language processing] [network analysis] [network congestion] [neuroscience] [newton] [noisy] [non-convex] [numerical] [object recognition] [occlusion] [occlusions] [optimization] [optimized] [over-sampling] [overview] [pancreas] [parallelization] [parameter] [parameters] [parsing] [pedestrian detection] [perceptron] [performance improvement] [personalize] [phoneme] [photonic] [physics] [pinterest] [plankton] [planning] [pose] [pre-training] [predicting] [prediction] [predictors] [probabilistic] [processor] [quantum] [random field] [random fields] [ranking] [rbm] [recommendation systems] [rectified] [rectifiers] [rectifiers:] [recurrent] [recurrent nets] [regression] [regularization] [reinforcement learning] [representation learning] [restricted boltzmann machine] [restricted boltzmann machines] [restricted bolzmann machines] [retail] [review] [road detection] [robot] [robotics] [robust] [sar data] [scene classification] [scene recognition] [scheduling] [sda] [search] [security] [segmentation] [semantic] [semantic indexing] [semantics] [semi-supervised] [sensor data] [sensory] [sentiment] [sentiment analysis] [sequence learning] [shape classification] [sigmoid] [sign language] [simulation] [sketch recognition] [smart city] [social] [soft computing] [softmax] [sound retrieval] [spam] [sparse] [sparsity] [spatial] [spatially] [spatio-temporal] [spectral] [speech] [speech recognition] [speech synthesis] [stochastic] [stochastic optimization] [structured networks] [study] [subspace analysis] [summarization] [supervised] [support vector machine] [support vector machines] [survey] [svm] [temporal] [term] [theory] [thermodynamics] [traffic] [traffic prediction] [traffic sign] [transcription] [transductive] [transfer learning] [tree structure] [tree structures] [twitter] [unsupervised] [user authentication] [user interface] [user interfaces] [vehicle][videos] [vision] [visual] [visual memory] [vocal] [vowel] [weather prediction] [web search] [weld] [word embeddings] [word sense]

2D

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. Dense 3d Face Alignment from 2d Videos in Real-Time

 

3D

  1. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  2. Inferring 3d Object Pose in Rgb-d Images
  3. Dense 3d Face Alignment from 2d Videos in Real-Time
  4. Learning Descriptors for Object Recognition and 3d Pose Estimation
  5. Fitting 3d Morphable Models using Local Features
  6. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  7. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  8. Iterative 3d shape classification by online metric learning

 

Acoustic

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Improving acoustic model for English Asr System using deep neural network
  5. Deep Neural Networks for Acoustic Modeling

 

Acoustic Model

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Improving acoustic model for English Asr System using deep neural network
  4. Deep Neural Networks for Acoustic Modeling

 

Action Recognition

  1. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  2. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  3. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  4. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach

 

Action Selection

  1. Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer

 

Activity Detection

  1. Neural Networks Based Methods for Voice Activity Detection in a Multi-room Domestic Environment

 

Adaptive

  1. Adaptive Road Detection via Context-aware Label Transfer
  2. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  3. Dynamic Feature-Adaptive Subdivision
  4. Deep Neural Programs for Adaptive Control in Cyber-Physical Systems
  5. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

Ads

  1. On optimizing machine learning workloads via kernel fusion

 

Adversarial Nets

  1. Conditional generative adversarial nets for convolutional face generation

 

Advertising

  1. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis

 

Aircraft Detection

  1. Aircraft Detection by Deep Convolutional Neural Networks

 

Algorithm

  1. Accelerated gradient temporal difference learning algorithms
  2. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  3. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  4. Exploring Latent Structure in Data: Algorithms and Implementations
  5. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  6. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  7. Cascade object detection with complementary features and algorithms
  8. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
  9. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification

 

Alzheimer’S

  1. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  2. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Applications

  1. Extreme learning machines: new trends and applications
  2. An Overview of Color Name Applications in Computer Vision
  3. Deep learning applications and challenges in big data analytics
  4. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  5. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  6. Multithreshold Entropy Linear Classifier: Theory and Applications

 

Approximate

  1. Single image super-resolution by approximated Heaviside functions
  2. Optimizing Neural Networks with Kronecker-factored Approximate Curvature

 

Architecture

  1. Scene Recognition by Manifold Regularized Deep Learning Architecture
  2. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  3. Universal Memory Architectures for Autonomous Machines
  4. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  5. A Minimal Architecture for General Cognition
  6. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  7. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

Articulatory Synthesis

  1. Data driven articulatory synthesis with deep neural networks

 

Autoencoder

  1. Training Stacked Denoising Autoencoders for Representation Learning
  2. Made: Masked Autoencoder for Distribution Estimation
  3. Convergence of gradient based pre-training in Denoising autoencoders
  4. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  5. Learning Classifiers from Synthetic Data Using a Multichannel Autoencoder
  6. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Autonomous

  1. Universal Memory Architectures for Autonomous Machines
  2. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Autonomously

  1. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Batch

  1. Efficient batchwise dropout training using submatrices
  2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

 

Batch Normalization

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

 

Batchwise

  1. Efficient batchwise dropout training using submatrices

 

Bayes

  1. Agnostic Bayes

 

Bayesian

  1. Interactions Between Gaussian Processes and Bayesian Estimation
  2. Towards Building Deep Networks with Bayesian Factor Graphs
  3. Scalable Bayesian Optimization Using Deep Neural Networks

 

Behavior Model

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Behavior Models

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Belief Propagation Networks

  1. Method and Apparatus for Spawning Specialist Belief Propagation Networks For Adjusting Exposure Settings

 

Big

  1. Random Bits Regression: a Strong General Predictor for Big Data
  2. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  3. Hypothesis Testing with Kernel Embeddings on Big and Interdependent Data
  4. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  5. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  6. Promises and Challenges of Big Data Computing in Health Sciences
  7. Deep learning applications and challenges in big data analytics
  8. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  9. Efficient Machine Learning for Big Data: A Review
  10. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Big Data

  1. Random Bits Regression: a Strong General Predictor for Big Data
  2. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  3. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  4. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  5. Promises and Challenges of Big Data Computing in Health Sciences
  6. Deep learning applications and challenges in big data analytics
  7. Efficient Machine Learning for Big Data: A Review
  8. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Big-Data

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Biologically

  1. Towards Biologically Plausible Deep Learning

 

Bird

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity

 

Blstm

  1. Text recognition using deep Blstm networks

 

Boosted

  1. Image classification using boosted local features with random orientation and location selection

 

Brain

  1. A spectrum of sharing: maximization of information content for brain imaging data
  2. Brain as an Emergent Finite Automaton: A Theory and Three Theorems
  3. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  4. Neuraledugaming: A Mathematical “Brain” to Make Digital Edugames Smart
  5. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Calibration

  1. Using Distance Estimation and Deep Learning to Simplify Calibration in Food Calorie Measurement

 

Cancer

  1. Automatic melanoma detection in dermatological images

 

Cascade

  1. Cascade object detection with complementary features and algorithms

 

Cell

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Equity-Minded Learning Environments: Pla as a Portal to Fostering Inclusive Excellence

 

Challenges

  1. Promises and Challenges of Big Data Computing in Health Sciences
  2. Deep learning applications and challenges in big data analytics

 

Character Recognition

  1. On the Performance Improvement of Devanagri Handwritten Character Recognition
  2. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

 

Classification

  1. DEFEATnet–A Deep Conventional Image Representation for Image Classification
  2. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  3. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  4. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  5. P300 classification using deep belief nets
  6. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  7. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  8. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  9. Constrained Extreme Learning Machines: A Study on Classification Cases
  10. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks
  11. Dynamic texture and scene classification by transferring deep image features
  12. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  13. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  14. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  15. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  16. Image Classification Using Generative Neuro Evolution for Deep Learning
  17. Imaging and representation learning of solar radio spectrums for classification
  18. Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification
  19. Deep learning for speech classification and speaker recognition
  20. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  21. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  22. Image classification using boosted local features with random orientation and location selection
  23. A novel pLSA based Traffic Signs Classification System
  24. Iterative 3d shape classification by online metric learning

 

Click-Through

  1. Deep Structured Semantic Model Produced Using Click-Through Data

 

Cloud

  1. A survey of research on cloud robotics and automation
  2. Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning
  3. Event Pattern Discovery on Ids Traces of Cloud Services
  4. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  5. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Clustered

  1. Deep Clustered Convolutional Kernels

 

Clustering

  1. Deep Learning with Nonparametric Clustering
  2. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  3. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  4. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  5. FaceNet: A Unified Embedding for Face Recognition and Clustering

 

Cnn

  1. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  2. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks

 

Coding Scheme

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization

 

Cognition

  1. Deep Image: Scaling up Image Recognition
  2. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  3. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  4. Neural Implementation of Probabilistic Models of Cognition
  5. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  6. Sign language recognition using convolutional neural networks
  7. Robust face recognition via transfer learning for robot partner
  8. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  9. On the Performance Improvement of Devanagri Handwritten Character Recognition
  10. HFirst: A Temporal Approach to Object Recognition
  11. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  12. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  13. Hierarchical Recognition System for Target Recognition from Sparse Representations
  14. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  15. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  16. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  17. Scene Recognition by Manifold Regularized Deep Learning Architecture
  18. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  19. Noisy Training for Deep Neural Networks in Speech Recognition
  20. Learning invariant object recognition from temporal correlation in a hierarchical network
  21. Deep Multimodal Learning for Audio-Visual Speech Recognition
  22. DeepID3: Face Recognition with Very Deep Neural Networks
  23. Freehand Sketch Recognition Using Deep Features
  24. Deep Neural Networks for Sketch Recognition
  25. Face frontalization for Alignment and Recognition
  26. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  27. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  28. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  29. A Hmax with Llc for visual recognition
  30. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  31. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  32. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  33. Robust Excitation-based Features For Automatic Speech Recognition
  34. Learning Descriptors for Object Recognition and 3d Pose Estimation
  35. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  36. Machine Learning in Automatic Speech Recognition: A Survey
  37. DigiRec Proposal: Handwritten Digit Recognition in Hardware
  38. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  39. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  40. Text recognition using deep Blstm networks
  41. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  42. Face Recognition Based on Deep Learning
  43. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  44. Learning Compact Binary Face Descriptor for Face Recognition
  45. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  46. Facial Expression Recognition via Deep Learning
  47. Domain Adaptation for Visual Recognition
  48. Subset based deep learning for Rgb-d object recognition
  49. Deep learning for speech classification and speaker recognition
  50. FaceNet: A Unified Embedding for Face Recognition and Clustering
  51. Speech emotion recognition with unsupervised feature learning
  52. A Minimal Architecture for General Cognition
  53. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  54. Scene Text Detection and Recognition: Recent Advances and Future Trends

 

Cognitive

  1. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom
  2. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Collaborative Filtering

  1. A Distributional Representation Model For Collaborative Filtering

 

Computer Vision

  1. An Overview of Color Name Applications in Computer Vision
  2. Deep learning of representations and its application to computer vision

 

Concept Learning

  1. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos

 

Constrained

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  2. Constrained Extreme Learning Machines: A Study on Classification Cases
  3. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators
  4. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Content-Based

  1. Utilizing Deep Learning for Content-based Community Detection

 

Controller

  1. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  2. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Convnet

  1. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition

 

Convnets

  1. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition

 

Convolutional

  1. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  2. Sign language recognition using convolutional neural networks
  3. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  4. Robust Tracking via Convolutional Networks without Learning
  5. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  6. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  7. End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning
  8. A Data-Reuse Aware Accelerator for Large-Scale Convolutional Networks
  9. Pedestrian Detection Via Pca Filters Based Convolutional Channel
  10. Aircraft Detection by Deep Convolutional Neural Networks
  11. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  12. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  13. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  14. Detectionn guided deconvolutional network for hierarchical feature learning
  15. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  16. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  17. Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
  18. Convolutional Fusion Network for Face Verification in the Wild
  19. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  20. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  21. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  22. Deep Clustered Convolutional Kernels
  23. Deep Convolutional Inverse Graphics Network
  24. A theoretical argument for complex-valued convolutional networks
  25. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  26. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos
  27. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  28. Deep convolutional networks for pancreas segmentation in Ct imaging
  29. Conditional generative adversarial nets for convolutional face generation
  30. Rotation-invariant convolutional neural networks for galaxy morphology prediction
  31. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015

 

Convolutional Network

  1. Robust Tracking via Convolutional Networks without Learning
  2. A Data-Reuse Aware Accelerator for Large-Scale Convolutional Networks
  3. Detectionn guided deconvolutional network for hierarchical feature learning
  4. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  5. A theoretical argument for complex-valued convolutional networks
  6. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Convolutional Neural Network

  1. Sign language recognition using convolutional neural networks
  2. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  3. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  4. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  5. Aircraft Detection by Deep Convolutional Neural Networks
  6. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  7. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  8. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  9. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  10. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks
  11. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  12. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  13. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos
  14. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  15. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Corpora

  1. Applying deep learning techniques on medical corpora from the World Wide Web: a prototypical system and evaluation
  2. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  3. On Using Monolingual Corpora in Neural Machine Translation

 

Ct

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  3. Stochastic Spectral Descent for Restricted Boltzmann Machines
  4. Explicit knowledge extraction in information-theoretic supervised multi-layered Som
  5. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  6. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  7. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  8. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  9. On the Performance Improvement of Devanagri Handwritten Character Recognition
  10. HFirst: A Temporal Approach to Object Recognition
  11. Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences
  12. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  13. Accurate localized short term weather prediction for renewables planning
  14. Utilizing Deep Learning for Content-based Community Detection
  15. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  16. Transductive Multi-view Zero-Shot Learning
  17. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  18. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  19. Video summarization based on Subclass Support Vector Data Description
  20. Retrieval Term Prediction Using Deep Belief Networks
  21. Scene Recognition by Manifold Regularized Deep Learning Architecture
  22. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  23. Neural Networks Based Methods for Voice Activity Detection in a Multi-room Domestic Environment
  24. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  25. An Effective Solution to Double Counting Problem in Human Pose Estimation
  26. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  27. Where am I? Predicting Montreal Neighbourhoods from Google Street View Images
  28. Learning invariant object recognition from temporal correlation in a hierarchical network
  29. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  30. Filtered Channel Features for Pedestrian Detection
  31. Deep Twin Support Vector Machine
  32. Pedestrian Detection Via Pca Filters Based Convolutional Channel
  33. A spectrum of sharing: maximization of information content for brain imaging data
  34. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  35. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  36. Interactions Between Gaussian Processes and Bayesian Estimation
  37. Aircraft Detection by Deep Convolutional Neural Networks
  38. Exploring Latent Structure in Data: Algorithms and Implementations
  39. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  40. Advanced Mean Field Theory of Restricted Boltzmann Machine
  41. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  42. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  43. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  44. Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
  45. Exploration of Deep Belief Networks for Vowel-like regions detection
  46. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  47. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  48. Continuous Hyper-parameter Learning for Support Vector Machines
  49. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  50. Human Interaction Recognition Using Independent Subspace Analysis Algorithm
  51. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  52. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  53. Adaptive Road Detection via Context-aware Label Transfer
  54. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  55. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  56. Detectionn guided deconvolutional network for hierarchical feature learning
  57. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  58. Fast Neural Networks with Circulant Projections
  59. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  60. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  61. ‘Hiring a Nashville sensation': using narrative learning to develop the problem solving skills of contract law students
  62. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  63. Inferring 3d Object Pose in Rgb-d Images
  64. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  65. Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships
  66. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  67. Towards Building Deep Networks with Bayesian Factor Graphs
  68. Abstract Learning via Demodulation in a Deep Neural Network
  69. Deep Transform: Error Correction via Probabilistic Re-Synthesis
  70. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  71. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  72. Principles of Explanatory Debugging to Personalize Interactive Machine Learning
  73. Universal Memory Architectures for Autonomous Machines
  74. Rectified Factor Networks
  75. Artificial intelligence: Learning to see and act
  76. Learning Descriptors for Object Recognition and 3d Pose Estimation
  77. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  78. Detecting spammers on social Networks
  79. Forecasting And Inventory Performance In Direct-store Delivery Supply Chain: Case Of Retailer In Serbia
  80. A Dictionary Approach to Ebsd Indexing
  81. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  82. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  83. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  84. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  85. Learning Semantic Hierarchies: A Continuous Vector Space Approach
  86. When Are Tree Structures Necessary for Deep Learning of Representations?
  87. Cascade object detection with complementary features and algorithms
  88. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  89. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  90. Two-Stage Learning to Predict Human Eye Fixations via SDAEs
  91. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  92. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis
  93. Predicting the Quality of User-Generated Answers Using Co-Training in Community-based Question Answering Portals
  94. Imaging and representation learning of solar radio spectrums for classification
  95. Robust people counting using sparse representation and random projection
  96. Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer
  97. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  98. Unsupervised word sense induction using rival penalized competitive learning
  99. Deep Human Parsing with Active Template Regression
  100. Learning Compact Binary Face Descriptor for Face Recognition
  101. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  102. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation
  103. Deep Reinforcement Learning for constructing meaning by ‘babbling’
  104. Subset based deep learning for Rgb-d object recognition
  105. Awareness, Integration and Interconnectedness Contemplative Practices of Higher Education Professionals
  106. Mask selective regularization for restricted Boltzmann machines
  107. Deep Structured Semantic Model Produced Using Click-Through Data
  108. Knowledge Representation for Image Feature Extraction
  109. Single image super-resolution by approximated Heaviside functions
  110. Automatic melanoma detection in dermatological images
  111. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”
  112. Predicting Entry-Level Categories
  113. Predicting Pinterest: Automating a distributed human computation
  114. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images
  115. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  116. A Minimal Architecture for General Cognition
  117. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  118. Feature maps driven no-reference image quality prediction of authentically distorted images
  119. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  120. Image classification using boosted local features with random orientation and location selection
  121. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  122. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications
  123. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  124. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications
  125. Scene Text Detection and Recognition: Recent Advances and Future Trends
  126. 3d Convolutional Neural Networks for Landing Zone Detection from LiDAR
  127. Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning
  128. Deep convolutional networks for pancreas segmentation in Ct imaging
  129. Deep Transform: Time-Domain Audio Error Correction via Probabilistic Re-Synthesis
  130. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview
  131. Learning Hypergraph-regularized Attribute Predictors
  132. Predicting ocean health, one plankton at a time
  133. Optimizing Neural Networks with Kronecker-factored Approximate Curvature
  134. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis
  135. Detection of Alzheimer’s disease using group lasso SVM-based region selection
  136. Vehicle Detection in Aerial Imagery: A small target detection benchmark
  137. Rotation-invariant convolutional neural networks for galaxy morphology prediction
  138. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015
  139. On Invariance and Selectivity in Representation Learning
  140. Rank Subspace Learning for Compact Hash Codes
  141. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder
  142. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Data Mining

  1. Ai for Data Mining

 

Data-Parallel

  1. Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning

 

Dataset

  1. Large-Scale Deep Learning on the Yfcc100m Dataset
  2. To Skip or not to Skip? A Dataset of Spontaneous Affective Response of Online Advertising (sara) for Audience Behavior Analysis

 

Dcnn

  1. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation

 

Decision Making

  1. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Deep Belief Nets

  1. P300 classification using deep belief nets

 

Deep Belief Network

  1. Retrieval Term Prediction Using Deep Belief Networks
  2. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  3. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  4. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks
  5. Exploration of Deep Belief Networks for Vowel-like regions detection
  6. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network
  7. Speech Separation based on Deep Belief Network
  8. Learning Document Semantic Representation with Hybrid Deep Belief Network

 

Deep Learning

  1. From multiple views to single view: a neural network approach

 

Deep Neural Network

  1. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  2. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Keystroke Dynamics Advances for Mobile Devices Using Deep Neural Network
  5. Noisy Training for Deep Neural Networks in Speech Recognition
  6. DeepID3: Face Recognition with Very Deep Neural Networks
  7. Deep Neural Networks for Sketch Recognition
  8. Over-Sampling in a Deep Neural Network
  9. Abstract Learning via Demodulation in a Deep Neural Network
  10. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  11. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  12. Scalable Bayesian Optimization Using Deep Neural Networks
  13. Sequence transcription with deep neural networks
  14. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  15. Improving acoustic model for English Asr System using deep neural network
  16. Deep Neural Networks for Acoustic Modeling
  17. Data driven articulatory synthesis with deep neural networks

 

Deep Sigmoid Belief Networks

  1. Learning Deep Sigmoid Belief Networks with Data Augmentation

 

Demodulation

  1. Abstract Learning via Demodulation in a Deep Neural Network

 

Denoising

  1. Training Stacked Denoising Autoencoders for Representation Learning
  2. Convergence of gradient based pre-training in Denoising autoencoders
  3. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  4. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Depression

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression

 

Depth-Videos

  1. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos

 

Diacritization

  1. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization

 

Dictionary

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  2. A Dictionary Approach to Ebsd Indexing

 

Dictionary Extraction

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity

 

Discriminative

  1. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  2. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  3. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  4. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  5. Learning Discriminative Feature Representations for Visual Categorization

 

Disease

  1. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  2. Pd Disease State Assessment in Naturalistic Environments using Deep Learning
  3. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Distributed

  1. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  2. Singa: A Distributed System for Deep Learning
  3. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation
  4. Predicting Pinterest: Automating a distributed human computation
  5. Implementation of a Practical Distributed Calculation System with Browsers and JavaScript, and Application to Distributed Deep Learning

 

Dnn

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition
  2. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments

 

Dropout

  1. Efficient batchwise dropout training using submatrices

 

Drug

  1. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features

 

Embedded

  1. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators

 

Emotion

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  3. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  4. Speech emotion recognition with unsupervised feature learning

 

Energy

  1. Quantum Energy Regression using Scattering Transforms
  2. Efficient Generation of Energy and Performance Pareto Front for Fpga Designs
  3. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters
  4. Big Data Analytic: Cases for Communications Systems Modeling and Renewable Energy Forecast

 

Ensemble Learning

  1. Soft sensor development for nonlinear and time‐varying processes based on supervised ensemble learning with improved process state partition

 

Entities

  1. Entity-centric search: querying by entities and for entities

 

Entity

  1. Entity-centric search: querying by entities and for entities

 

Error Correction

  1. Deep Transform: Error Correction via Probabilistic Re-Synthesis
  2. Deep Transform: Time-Domain Audio Error Correction via Probabilistic Re-Synthesis

 

Estimation

  1. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  2. An Effective Solution to Double Counting Problem in Human Pose Estimation
  3. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  4. Interactions Between Gaussian Processes and Bayesian Estimation
  5. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  6. Hands Deep in Deep Learning for Hand Pose Estimation
  7. Using Distance Estimation and Deep Learning to Simplify Calibration in Food Calorie Measurement
  8. Made: Masked Autoencoder for Distribution Estimation
  9. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  10. Learning Descriptors for Object Recognition and 3d Pose Estimation
  11. Deeply-Learned Feature for Age Estimation
  12. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  13. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Event

  1. Event Pattern Discovery on Ids Traces of Cloud Services
  2. Spike Event Based Learning in Neural Networks

 

Face

  1. Robust face recognition via transfer learning for robot partner
  2. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  3. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  4. DeepID3: Face Recognition with Very Deep Neural Networks
  5. Face frontalization for Alignment and Recognition
  6. Deep Representations for Iris, Face, and Fingerprint Spoofing Detection
  7. Dense 3d Face Alignment from 2d Videos in Real-Time
  8. Convolutional Fusion Network for Face Verification in the Wild
  9. Supervised descent method with low rank and sparsity constraints for robust face alignment
  10. Face Recognition Based on Deep Learning
  11. Learning Compact Binary Face Descriptor for Face Recognition
  12. FaceNet: A Unified Embedding for Face Recognition and Clustering
  13. Logistic Similarity Metric Learning For Face Verification
  14. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview
  15. Conditional generative adversarial nets for convolutional face generation

 

Face Recognition

  1. Robust face recognition via transfer learning for robot partner
  2. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?
  3. DeepID3: Face Recognition with Very Deep Neural Networks
  4. Face Recognition Based on Deep Learning
  5. Learning Compact Binary Face Descriptor for Face Recognition
  6. FaceNet: A Unified Embedding for Face Recognition and Clustering

 

Facial

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  2. Learning facial expressions from an image
  3. Facial Expression Recognition via Deep Learning
  4. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Feature

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  3. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  4. Learning features and their transformations from natural videos
  5. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  6. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  7. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  8. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  9. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  10. Filtered Channel Features for Pedestrian Detection
  11. Freehand Sketch Recognition Using Deep Features
  12. Dynamic texture and scene classification by transferring deep image features
  13. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  14. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  15. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  16. Detectionn guided deconvolutional network for hierarchical feature learning
  17. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  18. Dynamic Feature-Adaptive Subdivision
  19. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  20. Robust Excitation-based Features For Automatic Speech Recognition
  21. Deeply-Learned Feature for Age Estimation
  22. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  23. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  24. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  25. Cascade object detection with complementary features and algorithms
  26. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  27. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  28. On the Problem of Features Variability in Sequence Learning Problems
  29. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  30. Fitting 3d Morphable Models using Local Features
  31. Knowledge Representation for Image Feature Extraction
  32. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images
  33. Speech emotion recognition with unsupervised feature learning
  34. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  35. Learning Discriminative Feature Representations for Visual Categorization
  36. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  37. Feature maps driven no-reference image quality prediction of authentically distorted images
  38. Image classification using boosted local features with random orientation and location selection
  39. DeepContour: A Deep Convolutional Feature Learned by Positive-sharing Loss for Contour Detection draft version, Cvpr2015

 

Feature Discovery

  1. Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images

 

Feature Encoding

  1. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos

 

Feature Extraction

  1. Knowledge Representation for Image Feature Extraction

 

Feature Selection

  1. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters

 

Features

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Learning features and their transformations from natural videos
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Filtered Channel Features for Pedestrian Detection
  5. Freehand Sketch Recognition Using Deep Features
  6. Dynamic texture and scene classification by transferring deep image features
  7. Human Action Recognition Based on Recognition of Linear Patterns in Action Bank Features Using Convolutional Neural Networks
  8. Robust Excitation-based Features For Automatic Speech Recognition
  9. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  10. Cascade object detection with complementary features and algorithms
  11. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  12. On the Problem of Features Variability in Sequence Learning Problems
  13. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  14. Fitting 3d Morphable Models using Local Features
  15. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine
  16. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  17. Image classification using boosted local features with random orientation and location selection

 

Fine Tuning

  1. Statistical-mechanical analysis of pre-training and fine tuning in deep learning

 

Fine-Tuning

  1. DeepHash: Getting Regularization, Depth and Fine-Tuning Right

 

Fmri

  1. Deep learning of fMRI big data: a novel approach to subject-transfer decoding

 

Fpga

  1. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
  2. Efficient Generation of Energy and Performance Pareto Front for Fpga Designs

 

Fpga-Based

  1. Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks

 

Framework

  1. Hybrid Orthogonal Projection and Estimation (hope): A New Framework to Probe and Learn Neural Networks
  2. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework
  3. Emeuro: a framework for generating multi-purpose accelerators via deep learning
  4. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  5. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  6. Deep Learning Framework with Confused Sub-Set Resolution Architecture for Automatic Arabic Diacritization
  7. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Freehand

  1. Freehand Sketch Recognition Using Deep Features

 

Fuzzy Learning

  1. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery

 

Galaxy

  1. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Games

  1. Neuraledugaming: A Mathematical “Brain” to Make Digital Edugames Smart

 

Gaussian

  1. Interactions Between Gaussian Processes and Bayesian Estimation

 

Generative

  1. Image Classification Using Generative Neuro Evolution for Deep Learning
  2. GSNs: Generative Stochastic Networks
  3. Conditional generative adversarial nets for convolutional face generation

 

Genetic Programming

  1. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach

 

Gesture

  1. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Gradient

  1. Accelerated gradient temporal difference learning algorithms
  2. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  3. Gradient-based Hyperparameter Optimization through Reversible Learning
  4. Convergence of gradient based pre-training in Denoising autoencoders

 

Gradient-Based

  1. Gradient-based Hyperparameter Optimization through Reversible Learning

 

Graphical Model

  1. Hybrid Graphical Model for Semantic Image Segmentation

 

Graphics

  1. Deep Convolutional Inverse Graphics Network

 

Hand Pose

  1. Hands Deep in Deep Learning for Hand Pose Estimation

 

Handwritten

  1. On the Performance Improvement of Devanagri Handwritten Character Recognition
  2. DigiRec Proposal: Handwritten Digit Recognition in Hardware
  3. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition

 

Hardware

  1. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  2. DigiRec Proposal: Handwritten Digit Recognition in Hardware

 

Hash

  1. DeepHash: Getting Regularization, Depth and Fine-Tuning Right
  2. Deep learning with application to hashing
  3. Two Dimensional Hashing for Visual Tracking
  4. Shoe: Supervised Hashing with Output Embeddings
  5. Rank Subspace Learning for Compact Hash Codes

 

Hashing

  1. Deep learning with application to hashing
  2. Two Dimensional Hashing for Visual Tracking
  3. Shoe: Supervised Hashing with Output Embeddings

 

Hearing Aid

  1. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid

 

Hessian

  1. Subsampled Hessian Newton Methods for Su-pervised Learning

 

Hierarchical

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Hierarchical Recognition System for Target Recognition from Sparse Representations
  4. Learning invariant object recognition from temporal correlation in a hierarchical network
  5. Detectionn guided deconvolutional network for hierarchical feature learning
  6. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  7. Deep Hierarchical Parsing for Semantic Segmentation
  8. Hierarchical learning of grids of microtopics
  9. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech
  10. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

Hmax

  1. A Hmax with Llc for visual recognition
  2. 6 On Handling Occlusions Using Hmax

 

Hmm-Based

  1. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network

 

Hough Transform

  1. Complex-Valued Hough Transforms for Circles

 

Human Behavior

  1. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  2. A Hierarchical Neuro-Fuzzy Architecture for Human Behavior Analysis

 

Human Pose

  1. An Effective Solution to Double Counting Problem in Human Pose Estimation

 

Human-Level

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  2. Human-level control through deep reinforcement learning

 

Hyperspectral

  1. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  2. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  3. Deep Convolutional Neural Networks for Hyperspectral Image Classification

 

Image Classification

  1. DEFEATnet–A Deep Conventional Image Representation for Image Classification
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. An Improved Bilinear Deep Belief Network Algorithm for Image Classification
  4. Deep Convolutional Neural Networks for Hyperspectral Image Classification
  5. Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification
  6. Image Classification Using Generative Neuro Evolution for Deep Learning
  7. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  8. Image classification using boosted local features with random orientation and location selection

 

Image Recognition

  1. Deep Image: Scaling up Image Recognition

 

Imagery

  1. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  2. Vehicle Detection in Aerial Imagery: A small target detection benchmark

 

Imaging

  1. Machine learning for transient discovery in Pan-STARRS1 difference imaging
  2. A spectrum of sharing: maximization of information content for brain imaging data
  3. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  4. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  5. Imaging and representation learning of solar radio spectrums for classification
  6. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Indexing

  1. A Dictionary Approach to Ebsd Indexing

 

Information

  1. Deep Learning and the Information Bottleneck Principle

 

Information Retrieval

  1. Deep Sentence Embedding Using the Long Short Term Memory Network: Analysis and Application to Information Retrieval

 

Information-Theoretic

  1. Explicit knowledge extraction in information-theoretic supervised multi-layered Som

 

Invariant

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  2. Learning invariant object recognition from temporal correlation in a hierarchical network
  3. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  4. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Kernel

  1. On optimizing machine learning workloads via kernel fusion
  2. Hypothesis Testing with Kernel Embeddings on Big and Interdependent Data
  3. Deep Clustered Convolutional Kernels
  4. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  5. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Kernels

  1. Deep Clustered Convolutional Kernels
  2. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels

 

Lasso

  1. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Latent Structure

  1. Exploring Latent Structure in Data: Algorithms and Implementations

 

Learning To Rank

  1. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization

 

Lfw

  1. Naive-Deep Face Recognition: Touching the Limit of Lfw Benchmark or Not?

 

Linear Model

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Linear Models

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Logistic

  1. Logistic Similarity Metric Learning For Face Verification

 

Long Short-Term Memory

  1. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …

 

Lstm

  1. Text recognition using deep Blstm networks
  2. Compositional Distributional Semantics with Long Short Term Memory

 

Machine Translation

  1. Non-linear Learning for Statistical Machine Translation
  2. On Using Monolingual Corpora in Neural Machine Translation

 

Medical

  1. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  2. Applying deep learning techniques on medical corpora from the World Wide Web: a prototypical system and evaluation

 

Medicine

  1. Gender classification of subjects from cerebral blood flow changes using Deep Learning
  2. Automatic melanoma detection in dermatological images
  3. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Metric Learning

  1. Metric Learning

 

Mimd

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Missing

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition

 

Mobile

  1. Towards an Embodied Developing Vision System
  2. Keystroke Dynamics Advances for Mobile Devices Using Deep Neural Network
  3. 18.1 A 2.71 nJ/pixel 3D-stacked gaze-activated object-recognition system for low-power mobile Hmd applications

 

Monte Carlo

  1. Monte Carlo Integration Using Spatial Structure of Markov Random Field

 

Motion

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  3. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
  4. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  5. Speech emotion recognition with unsupervised feature learning

 

Mri

  1. Deep learning of fMRI big data: a novel approach to subject-transfer decoding
  2. Real-time Dynamic Mri Reconstruction using Stacked Denoising Autoencoder

 

Multi-Label

  1. Multi-label Learning with Missing Labels for Image Annotation and Facial Action Unit Recognition
  2. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels

 

Multicore

  1. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Natural Language Processing

  1. Deep Learning for Web Search and Natural Language Processing
  2. Open Domain Question Answering via Semantic Enrichment
  3. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
  4. Syntax-based Deep Matching of Short Texts
  5. Deep Multilingual Correlation for Improved Word Embeddings

 

Network Analysis

  1. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data

 

Network Congestion

  1. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

 

Neuroscience

  1. Computing brains: neuroscience, machine intelligence and big data in the cognitive classroom

 

Newton

  1. Subsampled Hessian Newton Methods for Su-pervised Learning

 

Noisy

  1. Noisy Training for Deep Neural Networks in Speech Recognition

 

Non-Convex

  1. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  2. On Graduated Optimization for Stochastic Non-Convex Problems

 

Numerical

  1. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework

 

Object Recognition

  1. HFirst: A Temporal Approach to Object Recognition
  2. Learning invariant object recognition from temporal correlation in a hierarchical network
  3. Learning Descriptors for Object Recognition and 3d Pose Estimation
  4. Heterogeneous Multi-column ConvNets with a Fusion Framework for Object Recognition
  5. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  6. Subset based deep learning for Rgb-d object recognition

 

Occlusion

  1. Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation
  2. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  3. 6 On Handling Occlusions Using Hmax

 

Occlusions

  1. Recognizing Multi-view Objects with Occlusions using a Deep Architecture
  2. 6 On Handling Occlusions Using Hmax

 

Optimization

  1. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM
  2. Inter-Tile Reuse Optimization Applied to Bandwidth Constrained Embedded Accelerators
  3. Gradient-based Hyperparameter Optimization through Reversible Learning
  4. RMSProp and equilibrated adaptive learning rates for non-convex optimization
  5. Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
  6. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework
  7. Scalable Bayesian Optimization Using Deep Neural Networks
  8. Denoising Autoencoders for fast Combinatorial Black Box Optimization
  9. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters
  10. On Graduated Optimization for Stochastic Non-Convex Problems

 

Optimized

  1. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  2. Jointly Optimized Regressors for Image Super-resolution

 

Over-Sampling

  1. Over-Sampling in a Deep Neural Network

 

Overview

  1. An Overview of Color Name Applications in Computer Vision
  2. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Pancreas

  1. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Parallelization

  1. A Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters

 

Parameter

  1. Continuous Hyper-parameter Learning for Support Vector Machines
  2. Gradient-based Hyperparameter Optimization through Reversible Learning
  3. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  4. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Parameters

  1. Application of Deep Neural Network in Estimation of the Weld Bead Parameters
  2. apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters

 

Parsing

  1. Deep Human Parsing with Active Template Regression
  2. Deep Hierarchical Parsing for Semantic Segmentation

 

Pedestrian Detection

  1. Improving Pedestrian Detection with Selective Gradient Self-Similarity Feature
  2. Taking a Deeper Look at Pedestrians
  3. Filtered Channel Features for Pedestrian Detection
  4. Pedestrian Detection Via Pca Filters Based Convolutional Channel

 

Perceptron

  1. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems

 

Performance Improvement

  1. On the Performance Improvement of Devanagri Handwritten Character Recognition

 

Personalize

  1. Principles of Explanatory Debugging to Personalize Interactive Machine Learning

 

Phoneme

  1. Implementation of Dnn-hmm Acoustic Models for Phoneme Recognition

 

Photonic

  1. Photonic Delay Systems as Machine Learning Implementations

 

Physics

  1. Enhanced Higgs Boson to τ+ τ− Search with Deep Learning

 

Pinterest

  1. Predicting Pinterest: Automating a distributed human computation

 

Plankton

  1. Predicting ocean health, one plankton at a time

 

Planning

  1. Accurate localized short term weather prediction for renewables planning
  2. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning

 

Pose

  1. An Effective Solution to Double Counting Problem in Human Pose Estimation
  2. Hands Deep in Deep Learning for Hand Pose Estimation
  3. Inferring 3d Object Pose in Rgb-d Images
  4. Emeuro: a framework for generating multi-purpose accelerators via deep learning
  5. Learning Descriptors for Object Recognition and 3d Pose Estimation
  6. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Pre-Training

  1. Statistical-mechanical analysis of pre-training and fine tuning in deep learning
  2. Convergence of gradient based pre-training in Denoising autoencoders

 

Predicting

  1. Where am I? Predicting Montreal Neighbourhoods from Google Street View Images
  2. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  3. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  4. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data
  5. Predicting the Quality of User-Generated Answers Using Co-Training in Community-based Question Answering Portals
  6. Predicting Entry-Level Categories
  7. Predicting Pinterest: Automating a distributed human computation
  8. Predicting ocean health, one plankton at a time
  9. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Prediction

  1. Accurate localized short term weather prediction for renewables planning
  2. Retrieval Term Prediction Using Deep Belief Networks
  3. Electronic Imaging & Signal Processing Automatic quality prediction of authentically distorted pictures
  4. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  5. Feature maps driven no-reference image quality prediction of authentically distorted images
  6. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  7. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  8. Rotation-invariant convolutional neural networks for galaxy morphology prediction

 

Predictors

  1. Learning Hypergraph-regularized Attribute Predictors

 

Probabilistic

  1. Deep Transform: Cocktail Party Source Separation via Probabilistic Re-Synthesis

 

Processor

  1. 4.6 A1. 93tops/w scalable deep learning/inference processor with tetra-parallel Mimd architecture for big-data applications

 

Quantum

  1. Quantum Energy Regression using Scattering Transforms

 

Random Field

  1. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  2. Conditional Random Fields as Recurrent Neural Networks

 

Random Fields

  1. Conditional Random Fields as Recurrent Neural Networks

 

Ranking

  1. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization

 

Rbm

  1. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  2. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception

 

Recommendation Systems

  1. A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems

 

Rectified

  1. Rectified Factor Networks

 

Rectifiers

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

 

Rectifiers:

  1. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

 

Recurrent

  1. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  2. Conditional Random Fields as Recurrent Neural Networks
  3. Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation
  4. Draw: A Recurrent Neural Network For Image Generation
  5. A hypothesize-and-verify framework for Text Recognition using Deep Recurrent Neural Networks
  6. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

 

Recurrent Nets

  1. Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

 

Regression

  1. Random Bits Regression: a Strong General Predictor for Big Data
  2. The Improvement of Structured-output Regression Forests on Detection about Face Parts⋆
  3. Quantum Energy Regression using Scattering Transforms
  4. Deep Human Parsing with Active Template Regression
  5. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech

 

Regularization

  1. DeepHash: Getting Regularization, Depth and Fine-Tuning Right
  2. Mask selective regularization for restricted Boltzmann machines

 

Reinforcement Learning

  1. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  2. Human-level control through deep reinforcement learning
  3. Deep Reinforcement Learning for constructing meaning by ‘babbling’
  4. Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning …

 

Representation Learning

  1. Training Stacked Denoising Autoencoders for Representation Learning
  2. End-to-End Photo-Sketch Generation via Fully Convolutional Representation Learning
  3. Imaging and representation learning of solar radio spectrums for classification
  4. Representation Learning with Deep Extreme Learning Machines for Efficient Image Set Classification
  5. Unsupervised domain adaptation via representation learning and adaptive classifier learning
  6. On Invariance and Selectivity in Representation Learning

 

Restricted Boltzmann Machine

  1. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  2. Stochastic Spectral Descent for Restricted Boltzmann Machines
  3. Advanced Mean Field Theory of Restricted Boltzmann Machine
  4. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  5. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  6. Fuzzy Restricted Boltzmann Machine and Its Fast Learning Algorithm
  7. Mask selective regularization for restricted Boltzmann machines
  8. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Restricted Boltzmann Machines

  1. An Evolutionary Approximation to Contrastive Divergence in Convolutional Restricted Boltzmann Machines
  2. Stochastic Spectral Descent for Restricted Boltzmann Machines
  3. Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)
  4. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
  5. Mask selective regularization for restricted Boltzmann machines
  6. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Restricted Bolzmann Machines

  1. L_1-regularized Boltzmann machine learning using majorizer minimization

 

Retail

  1. Forecasting And Inventory Performance In Direct-store Delivery Supply Chain: Case Of Retailer In Serbia

 

Review

  1. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  2. A Review of Methods for the Calculation of Solution Free Energies and the Modelling of Systems in Solution
  3. Unsupervised Deep Learning: A Short Review
  4. Efficient Machine Learning for Big Data: A Review

 

Road Detection

  1. Adaptive Road Detection via Context-aware Label Transfer

 

Robot

  1. A survey of research on cloud robotics and automation
  2. Robust face recognition via transfer learning for robot partner
  3. Robot team learning enhancement using Human Advice
  4. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  5. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Robotics

  1. A survey of research on cloud robotics and automation
  2. Hive Collective Intelligence for Cloud Robotics: A Hybrid Distributed Robotic Controller Design for Learning and Adaptation

 

Robust

  1. Robust face recognition via transfer learning for robot partner
  2. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  3. Robust Tracking via Convolutional Networks without Learning
  4. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  5. Robust Excitation-based Features For Automatic Speech Recognition
  6. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  7. Supervised descent method with low rank and sparsity constraints for robust face alignment
  8. Robust people counting using sparse representation and random projection
  9. Simple, Accurate, and Robust Nonparametric Blind Super-Resolution

 

Sar Data

  1. Urban Land Use and Land Cover Classification Using Remotely Sensed Sar Data through Deep Belief Networks

 

Scene Classification

  1. Dynamic texture and scene classification by transferring deep image features
  2. DLANet: A Manifold-Learning-based Discriminative Feature Learning Network for Scene Classification
  3. Sa-cnn: Dynamic Scene Classification using Convolutional Neural Networks

 

Scene Recognition

  1. Scene Recognition by Manifold Regularized Deep Learning Architecture

 

Scheduling

  1. Optimizing Scheduling of Refinery Operations based on Piecewise Linear Models

 

Sda

  1. Two-Stage Learning to Predict Human Eye Fixations via SDAEs

 

Search

  1. A survey of research on cloud robotics and automation
  2. Entity-centric search: querying by entities and for entities
  3. The Research on Cross-Language Emotion Recognition Algorithm for Hearing Aid
  4. Deep Learning for Web Search and Natural Language Processing
  5. Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research
  6. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”
  7. Enhanced Higgs Boson to τ+ τ− Search with Deep Learning
  8. Threshold concepts in the Scholarship of Teaching and Learning: a phenomenological study of educational leaders in a Canadian research-intensive university

 

Security

  1. Deep Learning of Behaviors for Security
  2. Replicating the Research of the Paper:“Application of Artificial Neural Network in Detection of Probing Attacks”

 

Segmentation

  1. Hybrid Graphical Model for Semantic Image Segmentation
  2. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  3. segDeepM: Exploiting Segmentation and Context in Deep Neural Networks for Object Detection
  4. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  5. Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation
  6. Deep Hierarchical Parsing for Semantic Segmentation
  7. Deep learning for automatic localization, identification, and segmentation of vertebral bodies in volumetric Mr images
  8. Deep convolutional networks for pancreas segmentation in Ct imaging

 

Semantic

  1. Hybrid Graphical Model for Semantic Image Segmentation
  2. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  3. Open Domain Question Answering via Semantic Enrichment
  4. Learning Semantic Hierarchies: A Continuous Vector Space Approach
  5. Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers
  6. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation
  7. Optimizing the Relevance-Redundancy Tradeoff for Efficient Semantic Segmentation
  8. Compositional Distributional Semantics with Long Short Term Memory
  9. Deep Hierarchical Parsing for Semantic Segmentation
  10. Deep Structured Semantic Model Produced Using Click-Through Data
  11. Learning Document Semantic Representation with Hybrid Deep Belief Network
  12. Lig at TRECVid 2014: Semantic Indexing

 

Semantic Indexing

  1. Lig at TRECVid 2014: Semantic Indexing

 

Semantics

  1. Compositional Distributional Semantics with Long Short Term Memory

 

Semi-Supervised

  1. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery
  2. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation

 

Sensor Data

  1. Predictive Analytics of Sensor Data Using Distributed Machine Learning Techniques
  2. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data

 

Sensory

  1. Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework

 

Sentiment

  1. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis
  2. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Sentiment Analysis

  1. Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis

 

Sequence Learning

  1. On the Problem of Features Variability in Sequence Learning Problems

 

Shape Classification

  1. Iterative 3d shape classification by online metric learning

 

Sigmoid

  1. Learning Deep Sigmoid Belief Networks with Data Augmentation

 

Sign Language

  1. Sign language recognition using convolutional neural networks

 

Simulation

  1. Using High-fidelity Simulation as a Learning Strategy in an Undergraduate Intensive Care Course
  2. Entrepreneurship Support Based on Mixed Bio-Artificial Neural Network Simulator (esbbann)

 

Sketch Recognition

  1. Freehand Sketch Recognition Using Deep Features
  2. Deep Neural Networks for Sketch Recognition

 

Smart City

  1. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City

 

Social

  1. Detecting spammers on social Networks
  2. Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features

 

Soft Computing

  1. An Evaluation of Deep Learning Miniature Concerning in Soft Computing

 

Softmax

  1. An Image Retrieval Method for Binary Images Based on Dbn and Softmax Classifier

 

Sound Retrieval

  1. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks

 

Spam

  1. Detecting spammers on social Networks

 

Sparse

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Hierarchical Recognition System for Target Recognition from Sparse Representations
  4. Sparse Neural Networks
  5. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  6. Robust people counting using sparse representation and random projection

 

Sparsity

  1. Analysis of Different Sparsity Methods in Constrained Rbm for Sparse Representation in Cognitive Robotic Perception
  2. Supervised descent method with low rank and sparsity constraints for robust face alignment

 

Spatial

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization
  2. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  3. Deep Convolutional Neural Networks for Object Extraction from High Spatial Resolution Remotely Sensed Imagery
  4. Monte Carlo Integration Using Spatial Structure of Markov Random Field
  5. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  6. Learning by Observation Using Qualitative Spatial Relations

 

Spatially

  1. Spatially Constrained Sparse Coding Scheme for Natural Scene Categorization

 

Spatio-Temporal

  1. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  2. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  3. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  4. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism

 

Spectral

  1. Stochastic Spectral Descent for Restricted Boltzmann Machines
  2. Multiclass feature learning for hyperspectral image classification: sparse and hierarchical solutions
  3. Spectral–Spatial Classification of Hyperspectral Data Based on Deep Belief Network
  4. Deep Convolutional Neural Networks for Hyperspectral Image Classification

 

Speech

  1. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Optimized multi-channel deep neural network with 2d graphical representation of acoustic speech features for emotion recognition
  4. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  5. Noisy Training for Deep Neural Networks in Speech Recognition
  6. Deep Multimodal Learning for Audio-Visual Speech Recognition
  7. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  8. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network
  9. Robust Excitation-based Features For Automatic Speech Recognition
  10. Machine Learning in Automatic Speech Recognition: A Survey
  11. Deep learning for speech classification and speaker recognition
  12. Speech Separation based on Deep Belief Network
  13. Speech emotion recognition with unsupervised feature learning
  14. Be at Odds? Deep and Hierarchical Neural Networks for Classification and Regression of Conflict in Speech

 

Speech Recognition

  1. Fast adaptation of deep neural network based on discriminant codes for speech recognition
  2. Acoustic Model Structuring for Improving Automatic Speech Recognition Performance
  3. Noisy Training for Deep Neural Networks in Speech Recognition
  4. Deep Multimodal Learning for Audio-Visual Speech Recognition
  5. A Fast Learning Method for the Multi-layer Perceptron in Automatic Speech Recognition Systems
  6. Robust Excitation-based Features For Automatic Speech Recognition
  7. Machine Learning in Automatic Speech Recognition: A Survey

 

Speech Synthesis

  1. F0 Modeling In Hmm-Based Speech Synthesis System Using Deep Belief Network

 

Stochastic

  1. Stochastic Spectral Descent for Restricted Boltzmann Machines
  2. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM
  3. On Graduated Optimization for Stochastic Non-Convex Problems
  4. GSNs: Generative Stochastic Networks

 

Stochastic Optimization

  1. Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM

 

Structured Networks

  1. Fully Connected Deep Structured Networks

 

Study

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Constrained Extreme Learning Machines: A Study on Classification Cases
  3. Predicting Alzheimer’s disease: a neuroimaging study with 3d convolutional neural networks
  4. Masterarbeit: Big Data and Machine Learning: A Case Study with Bump Boost
  5. Study on Binary Multilayer Neural Networks with Ebp Algorithm on Image Classification
  6. Threshold concepts in the Scholarship of Teaching and Learning: a phenomenological study of educational leaders in a Canadian research-intensive university

 

Subspace Analysis

  1. Human Interaction Recognition Using Independent Subspace Analysis Algorithm

 

Summarization

  1. Video summarization based on Subclass Support Vector Data Description
  2. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization
  3. Co-Regularized Deep Representations for Video Summarization

 

Supervised

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Explicit knowledge extraction in information-theoretic supervised multi-layered Som
  3. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  4. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  5. Extended Semi-supervised Fuzzy Learning Method for Nonlinear Outliers via Pattern Discovery
  6. Shoe: Supervised Hashing with Output Embeddings
  7. Weakly-and Semi-Supervised Learning of a Dcnn for Semantic Image Segmentation
  8. Unsupervised Deep Learning: A Short Review
  9. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  10. Unsupervised Deep Network Pretraining via Human Design
  11. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  12. Deep Transfer Network: Unsupervised Domain Adaptation
  13. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  14. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  15. Supervised descent method with low rank and sparsity constraints for robust face alignment
  16. Soft sensor development for nonlinear and time‐varying processes based on supervised ensemble learning with improved process state partition
  17. Unsupervised word sense induction using rival penalized competitive learning
  18. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  19. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
  20. Speech emotion recognition with unsupervised feature learning
  21. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

Support Vector Machine

  1. Deep Twin Support Vector Machine
  2. Continuous Hyper-parameter Learning for Support Vector Machines
  3. Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

 

Support Vector Machines

  1. Continuous Hyper-parameter Learning for Support Vector Machines

 

Survey

  1. A survey of research on cloud robotics and automation
  2. Transfer Learning using Computational Intelligence: A Survey
  3. Machine Learning in Automatic Speech Recognition: A Survey

 

Svm

  1. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews
  2. Detection of Alzheimer’s disease using group lasso SVM-based region selection

 

Temporal

  1. Accelerated gradient temporal difference learning algorithms
  2. Qualitative and Quantitative Spatio-Temporal Relations in Daily Living Activity Recognition
  3. HFirst: A Temporal Approach to Object Recognition
  4. Learning invariant object recognition from temporal correlation in a hierarchical network
  5. Scalable Hardware Efficient Deep Spatio-Temporal Inference Networks
  6. Method and System for Predicting Spatial and Temporal Distributions of Therapeutic Substance Carriers
  7. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach
  8. Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets
  9. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  10. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism

 

Term

  1. Accurate localized short term weather prediction for renewables planning
  2. Retrieval Term Prediction Using Deep Belief Networks
  3. Unidirectional Long Short-term Memory Recurrent Neural Network With Recurrent Output Layer For Low-latency Speech …
  4. Deep Sentence Embedding Using the Long Short Term Memory Network: Analysis and Application to Information Retrieval
  5. Compositional Distributional Semantics with Long Short Term Memory

 

Theory

  1. Advanced Mean Field Theory of Restricted Boltzmann Machine
  2. Brain as an Emergent Finite Automaton: A Theory and Three Theorems
  3. Deep Feature Selection: Theory and Application to Identify Enhancers and Promoters
  4. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  5. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory
  6. Multithreshold Entropy Linear Classifier: Theory and Applications

 

Thermodynamics

  1. Deep Unsupervised Learning using Nonequilibrium Thermodynamics

 

Traffic

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  2. Learning Driver Behavior Models from Traffic Observations for Decision Making and Planning
  3. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces
  4. An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City
  5. A novel pLSA based Traffic Signs Classification System

 

Traffic Prediction

  1. DeepSense: A novel learning mechanism for traffic prediction with taxi Gps traces

 

Traffic Sign

  1. Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature
  2. A novel pLSA based Traffic Signs Classification System

 

Transcription

  1. Sequence transcription with deep neural networks

 

Transductive

  1. Transductive Multi-view Zero-Shot Learning

 

Transfer Learning

  1. Robust face recognition via transfer learning for robot partner
  2. Transfer Learning using Computational Intelligence: A Survey

 

Tree Structure

  1. When Are Tree Structures Necessary for Deep Learning of Representations?

 

Tree Structures

  1. When Are Tree Structures Necessary for Deep Learning of Representations?

 

Twitter

  1. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data

 

Unsupervised

  1. Experimental Study of Unsupervised Feature Learning for HEp-2 Cell Images Clustering
  2. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  3. Unsupervised neural controller for Reinforcement Learning action-selection: Learning to represent knowledge
  4. Unsupervised Deep Learning: A Short Review
  5. Fingerprint Image Enhancement Using Unsupervised Hierarchical Feature Learning
  6. Unsupervised Deep Network Pretraining via Human Design
  7. Overcoming Intractability in Unsupervised Learning (Invited Talk)}}”, author = “S Arora, EW Mayr, N Ollinger
  8. Deep Transfer Network: Unsupervised Domain Adaptation
  9. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition
  10. Why Does Unsupervised Deep Learning WORK?-Aperspective From Group Theory
  11. Unsupervised word sense induction using rival penalized competitive learning
  12. Unsupervised Incremental Learning of Associative Cubes with Orthogonal Kernels
  13. Deep Unsupervised Learning using Nonequilibrium Thermodynamics
  14. Speech emotion recognition with unsupervised feature learning
  15. Unsupervised domain adaptation via representation learning and adaptive classifier learning

 

User Authentication

  1. Keystroke Dynamics User Authentication Using Advanced Machine Learning Methods

 

User Interface

  1. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

User Interfaces

  1. Modelling User Affect and Sentiment in Intelligent User Interfaces: A Tutorial Overview

 

Vehicle

  1. Vehicle Logo Recognition System Based on Convolutional Neural Networks With a Pretraining Strategy
  2. Vehicle Detection in Aerial Imagery: A small target detection benchmark

 

Video

  1. Learning features and their transformations from natural videos
  2. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  3. Video summarization based on Subclass Support Vector Data Description
  4. Co-Regularized Deep Representations for Video Summarization
  5. Dense 3d Face Alignment from 2d Videos in Real-Time
  6. Exploiting Feature and Class Relationships in Video Categorization with Regularized Deep Neural Networks
  7. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  8. Using Descriptive Video Services to Create a Large Data Source for Video Annotation Research
  9. Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism
  10. EmoNets: Multimodal deep learning approaches for emotion recognition in video
  11. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Videos

  1. Learning features and their transformations from natural videos
  2. Shape Feature Encoding via Fisher Vector for Efficient Fall Detection in Depth-Videos
  3. Dense 3d Face Alignment from 2d Videos in Real-Time
  4. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  5. Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos

 

Vision

  1. Towards an Embodied Developing Vision System

 

Visual

  1. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression
  2. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  3. Transferring Rich Feature Hierarchies for Robust Visual Tracking
  4. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments
  5. Deep Multimodal Learning for Audio-Visual Speech Recognition
  6. Two Dimensional Hashing for Visual Tracking
  7. A Hmax with Llc for visual recognition
  8. Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
  9. Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle
  10. The Neural-SIFT Feature Descriptor for Visual Vocabulary Object Recognition
  11. Automated Construction of Visual-Linguistic Knowledge via Concept Learning from Cartoon Videos
  12. DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking
  13. Learning Shared, Discriminative, and Compact Representations for Visual Recognition
  14. Domain Adaptation for Visual Recognition
  15. Learning Discriminative Feature Representations for Visual Categorization
  16. Exploring co-learning behavior of conference participants with visual network analysis of Twitter data
  17. I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions

 

Visual Memory

  1. Indexing Images for Visual Memory by Using Dnn Descriptors–Preliminary Experiments

 

Vocal

  1. Unsupervised dictionary extraction of bird vocalizations and new tools on assessing and visualizing bird activity
  2. Sound Retrieval From Vocal Imitation Queries Based On Deep Neural Networks

 

Vowel

  1. Exploration of Deep Belief Networks for Vowel-like regions detection

 

Weather Prediction

  1. Accurate localized short term weather prediction for renewables planning

 

Web Search

  1. Deep Learning for Web Search and Natural Language Processing

 

Weld

  1. Application of Deep Neural Network in Estimation of the Weld Bead Parameters

 

Word Embeddings

  1. Deep Multilingual Correlation for Improved Word Embeddings

 

Word Sense

  1. Unsupervised word sense induction using rival penalized competitive learning

 

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@misc{2015IPotamitis,
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@misc{2015JAHendersonTTAGibsonJWiles,
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@misc{2015JAMiñarroGiménezOMarínAlonsoMSamwald,
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@misc{2015JBaiYWuJZhangFChen,
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@misc{2015JBrunaSChintalaYLeCunSPiantinoASzlam,
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@misc{2015JDaiKHeJSun,
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@misc{2015JEslavaRios,
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@misc{2015JGaoXHeLDeng,
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@misc{2015JGauthier,
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@misc{2015JGirardMREmami,
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@misc{2015JHanDZhangSWenLGuoTLiuXLi,
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@misc{2015JHeaton,
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@misc{2015JHosangMOmranRBenensonBSchiele,
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@misc{2015JIbarzYBulatovIGoodfellow,
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@misc{2015JJohnsonZJiangMYanez,
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@misc{2015JKDuttaBBanerjee,
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@misc{2015JKONGKSUNMJIANGHHUOAYIMING,
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@misc{2015JKarhunenTRaikoKHCho,
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@misc{2015JKuenKMLimCPLee,
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@misc{2015JLiDJurafskyEHovy,
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@misc{2015JLiangKKelly,
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@misc{2015JLinOMorereVChandrasekharAVeillardHGoh,
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@misc{2015JLiuKZhaoBKusyJWenRJurdak,
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@misc{2015JLuVBehboodPHaoHZuoSXueGZhang,
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@misc{2015JLuVELiongXZhouJZhou,
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@misc{2015JMaRPSheridanALiawGDahlVSvetnik,
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@misc{2015JMansanetAAlbiolRParedesAAlbiol,
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@misc{2015JMartensRGrosse,
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@misc{2015JPadmanabhanMJJohnsonPremkumar,
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@misc{2015JSohlDicksteinEAWeissNMaheswaranathan,
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@misc{2015JSunWCaoZXuJPonce,
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@misc{2015JTayyubATavanaiYGatsoulisAGCohnDCHogg,
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@misc{2015JWHaKMKimBTZhang,
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@misc{2015JWeng,
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@misc{2015JYoungNHawes,
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@misc{2015JvandeWeijerFSKhan,
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@misc{2015KLiGQiJYeKAHua,
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@misc{2015KSelyuninDRatasichEBartocciRGrosu,
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@misc{2015KZhangQLiuYWuMHYang,
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@misc{2015LEBeerKRodriguezCTaylorNMartinezJones,
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@misc{2015LJDengWGuoTZHuang,
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@misc{2015LLWangNHCYung,
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@misc{2015LLiu,
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@misc{2015LLiuLShaoXLiKLu,
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@misc{2015LMcAfeeKOlukotun,
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@misc{2015LYaoATorabiKChoNBallasCPalHLarochelle,
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@misc{2015LZhengKIdrissiCGarciaSDuffnerABaskurt,
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@misc{2015MAlber,
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@misc{2015MAslanASengurYXiaoHWangMCInceXMa,
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@misc{2015MBackstromDCOOPER,
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@misc{2015MCicconetDGeigerMWerman,
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@misc{2015MDobrotaMVujošević,
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@misc{2015MGermainKGregorIMurrayHLarochelle,
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@misc{2015MGheisariMSBaghshah,
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@misc{2015MHaloi,
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@misc{2015MHermansMSorianoJDambrePBienstman,
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@misc{2015MKimLRigazio,
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@misc{2015MLessmannRPWürtz,
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@misc{2015MMNajafabadiFVillanustreTMKhoshgoftaar,
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@misc{2015MMSaleem,
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@misc{2015MNStolarMLechISBurnett,
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@misc{2015MOYahaya,
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@misc{2015MOberwegerPWohlhartVLepetit,
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@misc{2015MOhzeki,
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@misc{2015MOhzekiL_1-regularizedBoltzmannmachine,
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@misc{2015MPeemenBMesmanHCorporaal,
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@misc{2015MPeemenBMesmanHCorporaalInter-TileReuseOptimization,
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@misc{2015MProbst,
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@misc{2015MSGashlerZKindle,
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@misc{2015MSahasrabudhe,
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@misc{2015MSongZSunKLiuXLang,
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@misc{2015MThom,
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@misc{2015MUzairFShafaitBGhanemAMian,
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@misc{2015MWangZLuHLiQLiu,
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@misc{2015MWeinmannBJutziSHinzCMallet,
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@misc{2015MYLiuAMallyaOCTuzelXChen,
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@misc{2015MYasuda,
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@misc{2015MZhou,
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@misc{2015NJieBXiongzhuLZhongWYao,
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@misc{2015NJojicAPerinaDKim,
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@misc{2015NKarnaISuwardiNMaulidevi,
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@misc{2015NTishbyNZaslavsky,
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@misc{2015NWangSLiAGuptaDYYeung,
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@misc{2015NYHammerlaJMFisherPAndrasLRochester,
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@misc{2015OLemonAEshghi,
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@misc{2015PAgarwalAKumar,
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@misc{2015PKuhadAYassineSShirmohammadi,
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@misc{2015PLeWZuidema,
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@misc{2015PVerbancsicsJHarguess,
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@misc{2015QBNguyenTTVuCMLuong,
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@misc{2015QMaITanigawaMMurata,
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@misc{2015QWangJFangYYuan,
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@misc{2015RBahgat,
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@misc{2015RBruecknerBSchuller,
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@misc{2015RFuJGuoBQinWCheHWangTLiu,
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@misc{2015RGopalanRLiVMPatelRChellappa,
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@misc{2015RKSarvadevabhatlaRVBabu,
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@misc{2015RKamimura,
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@misc{2015SAnandaYogendran,
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@misc{2015SAroraEWMayrNOllinger,
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@misc{2015SAryalRGutierrezOsuna,
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@misc{2015SFenwick,
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@misc{2015SGMatthews,
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@misc{2015SGaoLDuanITsang,
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@misc{2015SGuptaPArbeláezRGirshickJMalik,
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@misc{2015SHuangHChenXDaiJChen,
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@misc{2015SHuangMElhoseinyAElgammalDYang,
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@misc{2015SIoffeCSzegedy,
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@misc{2015SJansen,
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@misc{2015SKoyamadaYShikauchiKNakaeMKoyamaSIshii,
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@misc{2015SRYoung,
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@misc{2015SRazakarivonyFJurie,
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@misc{2015XZhaoXShiSZhang,
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, , , , ,

About Amund Tveit (@atveit - amund@memkite.com)

Amund Tveit works in Memkite on developing large-scale Deep Learning and Search (Convolutional Neural Network) with Swift and Metal for iOS (see deeplearning.education for a Memkite app video demo). He also maintains the deeplearning.university bibliography (github.com/memkite/DeepLearningBibliography)

Amund previously co-founded Atbrox , a cloud computing/big data service company (partner with Amazon Web Services), also doing some “sweat equity” startup investments in US and Nordic startups. His presentations about Hadoop/Mapreduce Algorithms and Search were among top 3% of all SlideShare presentations in 2013 and his blog posts has been frequently quoted by Big Data Industry Leaders and featured on front pages of YCombinator News and Reddit Programming

He previously worked for Google, where he was tech.lead for Google News for iPhone (mentioned as “Google News Now Looks Beautiful On Your iPhone” on Mashable.com), lead a team measuring and improving Google Services in the Scandinavian Countries (Maps and Search) and worked as a software engineer on infrastructure projects. Other work experience include telecom (IBM Canada) and insurance/finance (Storebrand).

Amund has a PhD in Computer Science. His publications has been cited more than 500 times. He also holds 4 US patents in the areas of search and advertisement technology, and a pending US patent in the area of brain-controlled search with consumer-level EEG devices.

Amund enjoys coding, in particular Python, C++ and Swift (iOS)

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