Pytorch implementation of convolutional neural network visualization techniques
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Updated
Oct 10, 2022 - Python
Pytorch implementation of convolutional neural network visualization techniques
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
[ICCV 2017] Torch code for Grad-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)
PyTorch implementation of Grad-CAM, vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps
An implementation of Grad-CAM with keras
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...
Official implementation of Score-CAM in PyTorch
tensorflow implementation of Grad-CAM (CNN visualization)
A generalized gradient-based CNN visualization technique
Neural network visualization toolkit for tf.keras
Implementation of Grad CAM in tensorflow
TensorFlow implementations of visualization of convolutional neural networks, such as Grad-Class Activation Mapping and guided back propagation
InterpretDL: Interpretation of Deep Learning Models,基于『飞桨』的模型可解释性算法库。
[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.
Visualizations for understanding the regressed wheel steering angle for self driving cars
[ECCV 2018] code for Choose Your Neuron: Incorporating Domain Knowledge Through Neuron Importance
COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807
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