class-activation-map

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)

Attention-based Dropout Layer for Weakly Supervised Object Localization (CVPR 2019 Oral)

Time Series package for fastai v2

Class Activation Map (CAM) Visualizations in PyTorch.

The official code of Relevance-CAM

Attention \ Saliency maps and features visualization for deep learning models in pytorch

PyTorch implementation of "Learning Deep Features for Discriminative Localization"

Code for the paper : "Weakly supervised segmentation with cross-modality equivariant constraints", available at https://arxiv.org/pdf/2104.02488.pdf

High Resolution Class Activation Mapping for Discriminative Feature Localization

Implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation (Fong, et. al., 2018)

I'm planning to delve forward with understanding more about Computer Vision. Be a part of the journey, while I post my projects, knowledge snippets on the same. Happy Learning!

An application of CAM (Class Activation Maps) of CNNs. Localizes the food.

Generate class activation map for face images

Detection and localization of Asian hornets with a CNN using PyTorch

CAM algorithm implemented by python3 and pytorch 0.4.0

Code for our paper "Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism", by I. Gkartzonika, N. Gkalelis, V. Mezaris, presented and included in the Proceedings of the ECCV 2022 Workshop on Vision with Biased or Scarce Data (VBSD), Oct. 2022.

Generates class activation maps for CNN's with Global Average Pooling Layer Keras

Simple tf-keras code CAM (Class Activation Mapping)

Within the scope of this project, a classification model was builded whether lemons have good quality, bad quality or empty through data.

Through data, classification model was builded whether predicts if there is any crack or not on concrete with CAM.