_Index_of_Augmentation A survey on Image Data Augmentation for Deep Learning Adding noise Adversarial Spatial Dropout for Occlusion Alleviating Class Imbalance with Data Augmentation Attentive CutMix AttributeMix Augmentation-wise Weight Sharing strategy Augmented Random Search AugMix Auto Augment AutoAugment Co-Mixup Color Space Transformations CowMask Cropping Cut and Delete Cut and Mix Cut, Paste and Learn CutMix Cutout Data aug for spoken language Data Augmentation via Latent Space Interpolation for Image Classification Data Augmentation with Curriculum Learning Deep Generative Models Fast AutoAugment FeatMatch Feature Augmentation Feature Space Augmentation Flipping Fmix GAN‐based Data Augmentation Gaussian Distortion Geometric Transformations GridMask Hide and Seek Image Erasing Image Manipulation Image Mix Image Mixing and Deletion Intra-Class Part Swapping KeepAugment Kernel Filters Manifold MixUp ManifoldMix Meta Learning Data Augmentations Mixed Example Moment Exchange Neural Augmentation Noise Injection On the Importance of Visual Context for Data Augmentation in Scene Understanding Population Based Augmentation Puzzle Mix Random Distortion Random Erasing ReMix ResizeMix RICAP SaliencyMix Sample Pairing Shear Skew Tilt Smart Augmentation SmoothMix SMOTE SnapMix SpecAugment Test-time Augmentation Visual Context Augmentation