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)

An Explainable Neural Network for Fault Diagnosis With a Frequency Activation Map

Neural network visualization tool after an optional model compression with parameter pruning: (integrated) gradients, guided/visual backpropagation, activation maps for the cao model on the IndianPines dataset

Inception Modules with Connected Local and Global Features implemented with CAM.

Filter Visualizations, Heatmaps and Salience Maps

Class Activation Mapping

Activation maps visualizer for PyTorch

Paper Name: Utilizing Convolutional Neural Networks and Gradient-weighted Class Activation Mapping (Grad-CAM) for Dairy Cow Teat Image Classification. Testing the impact of CNN and Grad-CAM in the accuracy of dairy Cows Teat Imaga classification. Dataset and testing software from: https://github.com/YoushanZhang/SCTL

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.

PyTorch code for "SOLAR: Second-Order Loss and Attention for Image Retrieval". In ECCV 2020

Visualise Class activation mapping.