Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
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Updated
Jun 28, 2024 - Python
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
Official implementation of Score-CAM in PyTorch
Neural network visualization toolkit for tf.keras
A multi-functional library for full-stack Deep Learning. Simplifies Model Building, API development, and Model Deployment.
visualization:filter、feature map、attention map、image-mask、grad-cam、human keypoint、guided-backpro
vizgradcam is the fastest way to visualize GradCAM with your Keras models.
Gcam is an easy to use Pytorch library that makes model predictions more interpretable for humans. It allows the generation of attention maps with multiple methods like Guided Backpropagation, Grad-Cam, Guided Grad-Cam and Grad-Cam++.
tensorflow.keras implementation of gradcam and gradcam++
PyTorch implementation of pulse measurement neural networks.
Explainability of Deep Learning Models
Pytorch implementation of gradCAM, guidedBackProp, smoothGrad
A library that helps to explain AI models in a really quick & easy way
Weakly supervised Classification and Localization of Chest X-ray images
An API to better understand and visualize the inner workings of a CNN with GradCam; currently MobileNet
Applying GradCAM method with 3 kinds of CNN-based model for NLP classification task on french dataset.
This repository contains the PyTorch code for our ICIAP 2021 paper “Avoiding Shortcuts in Unpaired Image-to-Image Translation”.
PCA, t-SNE, Guided backpropagation, Grad-CAM on multi-label image classification with CelebA as dataset; CNN on digit classification with SVHN as dataset
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