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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

torch-cam

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)

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...

An implementation of Grad-CAM with keras

Official implementation of Score-CAM in PyTorch

Neural network visualization toolkit for tf.keras

tensorflow implementation of Grad-CAM (CNN visualization)

A generalized gradient-based CNN visualization technique

InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。

Implementation of Grad CAM in tensorflow

explainable-cnn

📦 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

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

🌈 📷 Gradient-weighted Class Activation Mapping (Grad-CAM) Demo

This repo contains Grad-CAM for 3D volumes.

COVID-CXNet

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

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