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)

A Simple pytorch implementation of GradCAM and GradCAM++

Neural network visualization toolkit for tf.keras

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++

Efficient explaining AI algorithms for Keras models

One of the first implementations of Grad-CAM ++ for time series / 1d signal.

Frame-agnostic XAI Library for Computer Vision, for understanding why models behave that way.

Weakly supervised Classification and Localization of Chest X-ray images

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

GradCAM++ and GradCAM for Fastai_v1.0

Analysis of visualization methods for relevant areas within images for a trained CNN. Used the GTSRB dataset as well as Activation Maximization, Saliency Map, GradCam, and Gradcam++ methods.

One of the firsts dataset level explanability libraries for 1d signal using GRAD-CAM++

Keras implementation of GradCam & GradCam++ to Dogs vs. Cats classification model

A web application that classifies an uploaded image into a disaster type, utilizing Angular

A tool for classifying an image into a disaster type, utilizing Python

Explainable AI for Image Classification