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Data Augmentation

3622 directly classified papers

Papers per year

Papers

Automatically augmenting an emotion dataset improves classification using audio EACL 2017
End-To-End Saliency Mapping via Probability Distribution Prediction CVPR 2016
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation AISTATS 2016
MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild NIPS 2016
Wavelet decompositions of Random Forests - smoothness analysis, sparse approximation and applications JMLR 2016
Pre-Translation for Neural Machine Translation COLING 2016
A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature COLING 2016
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing JMLR 2016
Improving English Conversational Telephone Speech Recognition INTERSPEECH 2016
Lig-Aikuma: A Mobile App to Collect Parallel Speech for Under-Resourced Language Studies INTERSPEECH 2016
Data Augmentation Using Multi-Input Multi-Output Source Separation for Deep Neural Network Based Acoustic Modeling INTERSPEECH 2016
An Iterative Phase Recovery Framework with Phase Mask for Spectral Mapping with an Application to Speech Enhancement INTERSPEECH 2016
Clustering High Dimensional Categorical Data via Topographical Features ICML 2016
Automatic Classification of Lexical Stress in English and Arabic Languages Using Deep Learning INTERSPEECH 2016
Convolutional Neural Networks with Data Augmentation for Classifying Speakers’ Native Language INTERSPEECH 2016
A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery ICML 2016
Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams ICML 2016
Prediction of Deception and Sincerity from Speech Using Automatic Phone Recognition-Based Features INTERSPEECH 2016
JCLAL: A Java Framework for Active Learning JMLR 2016
Random Rotation Ensembles JMLR 2016
BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition CVPR 2016
Stratified Sampling Meets Machine Learning ICML 2016
No Oops, You Won’t Do It Again: Mechanisms for Self-correction in Crowdsourcing ICML 2016
DisturbLabel: Regularizing CNN on the Loss Layer CVPR 2016
Active Learning for Delineation of Curvilinear Structures CVPR 2016