CAM, Grad-CAM, Grad-CAM++ and Guided Backpropagation post-hoc explanation methods
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Updated
Apr 30, 2024 - Jupyter Notebook
CAM, Grad-CAM, Grad-CAM++ and Guided Backpropagation post-hoc explanation methods
Filter visualization, Feature map visualization, Guided Backprop, GradCAM, Guided-GradCAM, Deep Dream
Implementation of GradCAM & Guided GradCAM with Tensorflow 2.x
Unofficial Pytorch implementation of guided backpropagation
AI for COVID-19
Computer vision visualization such as Grad-CAM, etc.
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
visualization:filter、feature map、attention map、image-mask、grad-cam、human keypoint、guided-backpro
Suite of methods that create attribution maps from image classification models.
Pytorch implementation of convolutional neural network visualization techniques
Public facing deeplift repo
Pytorch implementation of various neural network interpretability methods
PyTorch implementation of 'Vanilla' Gradient, Grad-CAM, Guided backprop, Integrated Gradients and their SmoothGrad variants.
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...
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++.
Implementation of Guided GradCAM in Keras
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 IndianPines dataset
In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
Use your classification neural network for object detection and localization
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