There are 11 repositories under grad-cam topic.
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
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
tensorflow implementation of Grad-CAM (CNN visualization)
Neural network visualization toolkit for tf.keras
A generalized gradient-based CNN visualization technique
Implementation of Grad CAM in tensorflow
InterpretDL: Interpretation of Deep Learning Models,基于『飞桨』的模型可解释性算法库。
📦 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.
This repo contains Grad-CAM for 3D volumes.
Visualizations for understanding the regressed wheel steering angle for self driving cars
COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807
[ECCV 2018] code for Choose Your Neuron: Incorporating Domain Knowledge Through Neuron Importance
In this part, I've introduced and experimented with ways to interpret and evaluate models in the field of image. (Pytorch)
Faster and more precisely than Grad-CAM
Official PyTorch implementation for our ICCV 2019 paper - Fooling Network Interpretation in Image Classification
Grad-CAM in TensorFlow, presented in Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.
Boundary box creation using a GradCAM heat-map from a pre-trained image classification model.
Efficient explaining AI algorithms for Keras models
Repository containing scripts to train and test a neural network whose goal is to detect presence of COVID-19
A customizable lightweight Grad-CAM implementation