Popular GitHub Repositories for Grad Cam

Pytorch implementation of convolutional neural network visualization techniques

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)

pytorch实现Grad-CAM和Grad-CAM++,可以可视化任意分类网络的Class Activation Map (CAM)图,包括自定义的网络;同时也实现了目标检测faster r-cnn和retinanet两个网络的CAM图;欢迎试用、关注并反馈问题...

tensorflow implementation of Grad-CAM (CNN visualization)

A generalized gradient-based CNN visualization technique

TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propagation

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

This repo contains Grad-CAM for 3D volumes.

Implementation of Grad-CAM for text.

Faster and more precisely than Grad-CAM

Official PyTorch implementation for our ICCV 2019 paper - Fooling Network Interpretation in Image Classification

About face technology

GiMeFive: Towards Interpretable Facial Emotion Classification ?????? (PyTorch Implementation)

This repo shows how to classify crack images and discuss the result with grad-cam

saliency map, adversarial image, (gradient) class activation map

基于Blender生成的合成数据、ConvNeXt卷积神经网络、Grad-CAM可视化技术和FastAPI框架的端到端工业零件分类系统，并使用Docker进行完全容器化，实现实时推理。

classify images as AI-generated art or Real art using a fine-tuned MobileNetV2 model. The model utilizes transfer learning to achieve high accuracy and interpretability through Grad-CAM visualizations

This repository is the code basis for the paper titled "Balancing Privacy and Explainability in Federated Learning"

Improvising adversarial attack against prediction of neural network

Research on AutoML and Explainability．