class-activation-maps

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

[CVPRW 2020] Official implementation of Score-CAM in Pytorch

Class-Weighted Convolutional Features for Image Retrieval (BMVC 2017)

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

Class Activation Map using Keras

Deep functional residue identification

COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807

I implemented a detection algorithm with a classification data set that does not have annotation information for the bounding box. Based on resnet50 network, I implemented text detector using class activation mapping method.

Visualizing where the Convolution Network is looking through CAM.

Evaluating surgical skills from kinematic data using convolutional neural networks

VGG transfer learning and Class Activation Mapping

This project propose a simple example to expose the implicit attention of Convolutional Neural Networks on the image.

Scripts that utilize class activation maps and self-attention layers within Keras models to classify faces from FEI Faces Dataset

This repository introduces different Explainable AI approaches and demonstrates how they can be implemented with PyTorch and torchvision. Used approaches are Class Activation Mappings, LIMA and SHapley Additive exPlanations.

Visualizing Class Activation Maps for Convolutional Neural Networks

Tutorial to show how to extract object localization

Weakly supervised Classification and Localization of Chest X-ray images

Building a multi-label classifier from scratch and using transfer learning for the PASCAL VOC image dataset.

A Deep Learning Humerus Bone Fracture Detection Model which classifies a broken humerus bone X-ray image from a normal X-ray image with no fracture using Back Propagation, Regularization, Convolutional Neural Networks (CNN), Auto-Encoders (AE) and Transfer Learning.

MVA Master School Project - Weakly Supervised Semantic Segmentation

Repository containing code to run Score-CAM algorithm available on https://arxiv.org/pdf/1910.01279v1.pdf.

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

Generates class activation maps for CNN's with Global Average Pooling Layer Keras

Class activation maps for high risk and low risk patients in lung adenocarcinoma

Similarity Differences and Uniqueness Explainable AI method

High Resolutions Class Activation Maps usage script. Implementation from HR-CAM paper.