PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)
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Jan 21, 2020 - Python
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occlusion-sensitivity
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Pytorch implementation of various neural network interpretability methods
pytorch deepdream saliency-map occlusion-sensitivity smoothgrad guided-backpropagation interpretable-deep-learning lrp gradient-visualization interpretable gradcam deconvnet cnn-visualization deeplift integrated-gradients activation-maximization interpretability-methods uncertainty-interpretability taylor-decomposition nn-interpretability
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Mar 8, 2022 - Jupyter Notebook
This script evaluates the sensitivity of VGG-16 to occlusion using Keras
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Nov 9, 2016 - Python
Visualizing and interpreting features of CNN model
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Jul 2, 2018 - Python
Explainable AI in Intrusion Detection
machine-learning machine-learning-algorithms python3 intrusion-detection random-forest-classifier explainable-artificial-intelligence occlusion-sensitivity explainable-ai explainable-ml explainable-machine-learning
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May 25, 2024 - Jupyter Notebook
A CNN model developed to observe and predict lung related chronic diseases at an early stage. ResNet-50 architecture is used to classify x-ray images and Occlusion Sensitivity Function is used to visualise the image with its affected areas.
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Dec 28, 2024 - Python
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