#Grad-cam
Showing 16 of 16 repositories tagged #grad-cam, ranked by stars
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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)
[ICCV 2017] Torch code for Grad-CAM
PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)
An implementation of Grad-CAM with keras
Neural network visualization toolkit for tf.keras
tensorflow implementation of Grad-CAM (CNN visualization)
Implementation of Grad CAM in tensorflow
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propagation
COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807
Visualizations for understanding the regressed wheel steering angle for self driving cars
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++.
Attribution methods that explain image classification models, implemented in PyTorch, and support batch inputs and GPU.
Faster and more precisely than Grad-CAM