Data Augmentation Publications

Publications in Data Augmentation

Explore the most influential research papers and scholarly works that have shaped Data Augmentation. Use the concept filter below to focus on a specific sub-area of research.

Data Augmentation

7.2K

Publications

637K

Citations

Showing yearly statistics from 2000-2026.

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	Year	Citations
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy arXiv (Cornell University) Data AugmentationDeep Neural NetworksMachine VisionMachine LearningData Science	2015	24.2K
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He, Xiangyu Zhang, Shaoqing Ren, Convolutional Neural NetworkEngineeringMachine LearningAutoencodersImagenet Classification	2015	18.4K
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe arXiv (Cornell University) Data AugmentationDeep Neural NetworksMachine VisionMachine LearningData Science	2024	15.6K
A survey on Image Data Augmentation for Deep Learning Connor Shorten, Taghi M. Khoshgoftaar Journal Of Big Data Convolutional Neural NetworkEngineeringMachine LearningAutoencodersImage Analysis	2019	11.6K
YOLOv4: Optimal Speed and Accuracy of Object Detection Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao arXiv (Cornell University) Data AugmentationConvolutional Neural NetworkMachine VisionImage AnalysisMachine Learning	2020	10.4K
Decoupled Weight Decay Regularization Ilya Loshchilov, Frank Hutter arXiv (Cornell University) EngineeringMachine LearningWeight DecayAtomic DecompositionImage Analysis	2017	9K
Explaining and Harnessing Adversarial Examples Ian Goodfellow, Jonathon Shlens, Christian Szegedy arXiv (Cornell University) Artificial IntelligenceData AugmentationMaxout NetworkEngineeringMachine Learning	2014	8.1K
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Convolutional Neural NetworkEngineeringMachine LearningDeep Belief NetworksAutoencoders	2010	5K
mixup: Beyond Empirical Risk Minimization Hongyi Zhang, Moustapha Cissé, Yann Dauphin, arXiv (Cornell University) Artificial IntelligenceConvolutional Neural NetworkEngineeringMachine LearningNeural Network	2017	4.7K
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Proceedings of the AAAI Conference on Artificial Intelligence Convolutional Neural NetworkEngineeringMachine LearningAutoencodersResidual Inception Networks	2017	4.5K
CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features Sangdoo Yun, Dongyoon Han, Sanghyuk Chun, Regional DropoutConvolutional Neural NetworkEngineeringMachine LearningImage Classification	2019	4.5K
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot, Patrick McDaniel, Somesh Jha, Artificial IntelligenceData AugmentationDeep Neural NetworksMachine VisionMachine Learning	2016	3.8K

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