guided-backpropagation

Pytorch implementation of convolutional neural network visualization techniques

Public facing deeplift repo

PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)

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...

📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.

#计算机科学#TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propagation

visualization：filter、feature map、attention map、image-mask、grad-cam、human keypoint、guided-backpro

Pytorch implementation of various neural network interpretability methods

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-...

#计算机科学#In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)

Filter visualization, Feature map visualization, Guided Backprop, GradCAM, Guided-GradCAM, Deep Dream

Implementation of GradCAM & Guided GradCAM with Tensorflow 2.x

#计算机科学#PyTorch implementation of 'Vanilla' Gradient, Grad-CAM, Guided backprop, Integrated Gradients and their SmoothGrad variants.

Use your classification neural network for object detection and localization

This repository contains all my theroy reports, written assignments and programming code that I wrote/referrd for the DL course at IIT,Madras taught my advisor Prof.Mitesh Khapra.

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 IndianPine...

Part of the experiments in "A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations"

Suite of methods that create attribution maps from image classification models.

Implementation of Guided GradCAM in Keras

Computer vision visualization such as Grad-CAM, etc.