Data Augmentation

Data augmentation involves techniques used for increasing the amount of data, based on different modifications, to expand the amount of examples in the original dataset. Data augmentation not only helps to grow the dataset but it also increases the diversity of the dataset. When training machine learning models, data augmentation acts as a regularizer and helps to avoid overfitting.

Data augmentation techniques have been found useful in domains like NLP and computer vision. In computer vision, transformations like cropping, flipping, and rotation are used. In NLP, data augmentation techniques can include swapping, deletion, random insertion, among others.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 7226–7250 of 8378 papers

Title	Date	Tasks	Status	Hype
Schema-Guided Dialogue State Tracking Task at DSTC8	Feb 2, 2020	Data AugmentationDialogue State Tracking	CodeCode Available	1
Efficient Model for Image Classification With Regularization Tricks	Feb 1, 2020	ClassificationData Augmentation	CodeCode Available	1
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy	Jan 31, 2020	Data AugmentationImage Augmentation	—Unverified	0
Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blending	Jan 31, 2020	Data Augmentation	—Unverified	0
Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification Frameworks	Jan 30, 2020	Data AugmentationGeneral Classification	CodeCode Available	0
BUT Opensat 2019 Speech Recognition System	Jan 30, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Real-Time Well Log Prediction From Drilling Data Using Deep Learning	Jan 28, 2020	Data AugmentationFeature Engineering	—Unverified	0
FakeLocator: Robust Localization of GAN-Based Face Manipulations	Jan 27, 2020	Data AugmentationFace Generation	—Unverified	0
Imperfect ImaGANation: Implications of GANs Exacerbating Biases on Facial Data Augmentation and Snapchat Selfie Lenses	Jan 26, 2020	Data AugmentationFace Generation	—Unverified	0
Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas	Jan 26, 2020	Data AugmentationTranslation	CodeCode Available	0
Model Averaging and Augmented Inference for Stable Echocardiography Segmentation using 2D ConvNets	Jan 25, 2020	Data Augmentation	—Unverified	0
Effect of GAN augmented dataset size on deep learning-based ultrasound bone segmentation model training	Jan 25, 2020	Data AugmentationDeep Learning	—Unverified	0
Morphological Signature for Improvement of Weakly Supervised Segmentation of Quadriceps Muscles on Magnetic Resonance Imaging Data	Jan 25, 2020	Data AugmentationMedical Diagnosis	—Unverified	0
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective	Jan 25, 2020	Data AugmentationSegmentation	CodeCode Available	1
Data Techniques For Online End-to-end Speech Recognition	Jan 24, 2020	Data AugmentationDomain Adaptation	—Unverified	0
Stochastic Optimization of Plain Convolutional Neural Networks with Simple methods	Jan 24, 2020	Data AugmentationImage Classification	CodeCode Available	0
PDE-based Group Equivariant Convolutional Neural Networks	Jan 24, 2020	Data AugmentationGPU	CodeCode Available	0
Semi-supervised ASR by End-to-end Self-training	Jan 24, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Fish Detection Using Deep Learning	Jan 23, 2020	Data AugmentationDeep Learning	—Unverified	0
Variational Hierarchical Dialog Autoencoder for Dialog State Tracking Data Augmentation	Jan 23, 2020	Data Augmentationdialog state tracking	CodeCode Available	0
Cloud and Cloud Shadow Segmentation for Remote Sensing Imagery via Filtered Jaccard Loss Function and Parametric Augmentation	Jan 23, 2020	Cloud DetectionData Augmentation	CodeCode Available	1
Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard	Jan 20, 2020	Data AugmentationLanguage Modeling	—Unverified	0
Synthetic Magnetic Resonance Images with Generative Adversarial Networks	Jan 17, 2020	Data Augmentation	CodeCode Available	0
Interpreting Galaxy Deblender GAN from the Discriminator's Perspective	Jan 17, 2020	AstronomyData Augmentation	—Unverified	0
BSUV-Net: A Fully-Convolutional Neural Network forBackground Subtraction of Unseen Videos	Jan 14, 2020	Data AugmentationObject Tracking	CodeCode Available	1

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All datasets ImageNet CIFAR-10 GA1457

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeiT-B (+MixPro)	Accuracy (%)	82.9	—	Unverified
2	ResNet-200 (DeepAA)	Accuracy (%)	81.32	—	Unverified
3	DeiT-S (+MixPro)	Accuracy (%)	81.3	—	Unverified
4	ResNet-200 (Fast AA)	Accuracy (%)	80.6	—	Unverified
5	ResNet-200 (UA)	Accuracy (%)	80.4	—	Unverified
6	ResNet-200 (AA)	Accuracy (%)	80	—	Unverified
7	ResNet-50 (DeepAA)	Accuracy (%)	78.3	—	Unverified
8	ResNet-50 (TA wide)	Accuracy (%)	78.07	—	Unverified
9	ResNet-50 (LoRot-E)	Accuracy (%)	77.72	—	Unverified
10	ResNet-50 (LoRot-I)	Accuracy (%)	77.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	WideResNet-40-2 (Faster AA)	Percentage error	3.7	—	Unverified
2	Shake-Shake (26 2×32d) (Faster AA)	Percentage error	2.7	—	Unverified
3	WideResNet-28-10 (Faster AA)	Percentage error	2.6	—	Unverified
4	Shake-Shake (26 2×112d) (Faster AA)	Percentage error	2	—	Unverified
5	Shake-Shake (26 2×96d) (Faster AA)	Percentage error	2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiffAug	Classification Accuracy	92.7	—	Unverified
2	PaCMAP	Classification Accuracy	85.3	—	Unverified
3	hNNE	Classification Accuracy	77.4	—	Unverified
4	TopoAE	Classification Accuracy	74.6	—	Unverified