This repository trains model to perform object localization task on Pets Dataset and visualizes the CNN filters.
- Guided Backpropagation (GBP)
- Integrated Gradients (IG)
- Smooth-Guided Backpropagation
- Smooth-Integrated Gradients
- Grad-CAM
- Activation Maximization
- Local Interpretable Model-agnostic Explanations (LIME)
- DeepExplainer - SHapley Additive exPlanations (SHAP) + DeepLIFT
- GradientExplainer - SHAP + IG + SmoothGrad
[1] https://keras.io/examples/vision/visualizing_what_convnets_learn/
[2] https://jacobgil.github.io/deeplearning/filter-visualizations
[3] https://www.kaggle.com/vincentman0403/visualize-output-of-cnn-filter-by-gradient-ascent
[4] https://medium.com/@jon.froiland/convolutional-neural-networks-part-8-3ac54c9478cc
[5] https://github.com/sicara/tf-explain#available-methods
[6] Cristian Vasta, Deep Learning Models with Tensorflow 2.0, Available at: https://morioh.com/p/64064daff26c, Accessed on: 03. 05. 2021.
[7] Hoa Nguyen, CNN Visualization Keras TF2, GitHub, Available at: https://github.com/nguyenhoa93/cnn-visualization-keras-tf2, Accessed on: 03. 05. 2021.
[8] Available at: https://pair-code.github.io/saliency/#guided-ig