Augmentation
Methods
- Attentive CutMix
- AttributeMix
- AugMix
- GridMask
- Hide and Seek
- Image Mixing and Deletion
- Intra-Class Part Swapping
- Puzzle Mix
- KeepAugment
- RICAP
- RandAugment
- Random Distortion
- Random Erasing
- ReMix
- ResizeMix
- SMOTE
- SaliencyMix
- Sample Pairing
- Visual Context Augmentation
- SmoothMix
- SnapMix
- SpecAugment
- Co-Mixup
- Cut and Mix
- Data Augmentation via Latent Space Interpolation for Image Classification
- Data Augmentation with Curriculum Learning
Disadvantages
XAI
Methods
- Adaptive Whitening Saliency
- Bayesian Rule List
- CAM
- Conductance
- DeconvNet
- Deep Inside Convolutional Networks
- Deep Visual Explanation
- DeepFool
- DeepLIFT
- Dynamic visual attention
- Embedding Human Knowledge into Deep Neural Network via Attention Map
- Generalizing Adversarial Explanations with Grad-CAM
- Graph-based visual saliency
- Guided BackProp
- Guided GradCAM
- Influence of image classification accuracy on saliency map estimation
- Integrated Gradients
- Interpretation of Neural networks is fragile
- Noise Tunnel
- On the overlap between Grad-CAM saliency maps and explainable visual features in skin cancer images
- RISE
- Real Time Image Saliency for Black Box Classifiers
- SAM-ResNet
- SDR
- SP-LIME
- Salience Map
- Smooth-Grad
- SmoothGrad Square
- Summit
- VarGrad
- ScoreCAM