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.
-
Updated
Jan 1, 2021
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 first implementations of Grad-CAM ++ for time series / 1d signal.
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
GradCAM++ and GradCAM for Fastai_v1.0
One of the firsts dataset level explanability libraries for 1d signal using GRAD-CAM++
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Frame-agnostic XAI Library for Computer Vision, for understanding why models behave that way.
Explainable AI for Image Classification
Efficient explaining AI algorithms for Keras models
Weakly supervised Classification and Localization of Chest X-ray images
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++
Neural network visualization toolkit for tf.keras
A Simple pytorch implementation of GradCAM and GradCAM++
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)
Add a description, image, and links to the gradcam-plus-plus topic page so that developers can more easily learn about it.
To associate your repository with the gradcam-plus-plus topic, visit your repo's landing page and select "manage topics."