Class Activation Map | Stanford Cars | PyTorch
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Updated
Jan 5, 2023 - Python
Class Activation Map | Stanford Cars | PyTorch
Generates class activation maps for CNN's with Global Average Pooling Layer Keras
Simple tf-keras code CAM (Class Activation Mapping)
Classification model was builded whether lemons have good quality, bad quality or have empty background with Class Activation Map.
Through data, classification model was builded whether predicts if there is any crack or not on concrete with Class Activation Map.
Explainable text classification
Unofficial PyTorch implementation of Score-CAM with additional functions
Generate class activation map for face images
CAM algorithm implemented by python3 and pytorch 0.4.0
An application of CAM (Class Activation Maps) of CNNs. Localizes the food.
Detection and localization of Asian hornets with a CNN using PyTorch
Computer vision visualization such as Grad-CAM, etc.
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.
An awesome list of papers and tools about the class activation map (CAM) technology.
Attribution methods that explain image classification models, implemented in PyTorch, and support batch input and GPU.
Implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation (Fong, et. al., 2018)
Building models that can predict whether an area is at risk of a wildfire or not on satellite images.
High Resolution Class Activation Mapping for Discriminative Feature Localization
[SIGMOD 2022] Python code for "Dimension-wise Class Activation Map for Multivariate Time Series Classification"
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