An application of CAM (Class Activation Maps) of CNNs. Localizes the food.
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Updated
Sep 14, 2018 - Jupyter Notebook
An application of CAM (Class Activation Maps) of CNNs. Localizes the food.
CAM algorithm implemented by python3 and pytorch 0.4.0
Generate class activation map for face images
Generates class activation maps for CNN's with Global Average Pooling Layer Keras
Attention-based Dropout Layer for Weakly Supervised Object Localization (CVPR 2019 Oral)
Attention \ Saliency maps and features visualization for deep learning models in pytorch
Class Activation Map (CAM) Visualizations in PyTorch.
High Resolution Class Activation Mapping for Discriminative Feature Localization
Detection and localization of Asian hornets with a CNN using PyTorch
Explainable text classification
Implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation (Fong, et. al., 2018)
Simple tf-keras code CAM (Class Activation Mapping)
Code for the paper : "Weakly supervised segmentation with cross-modality equivariant constraints", available at https://arxiv.org/pdf/2104.02488.pdf
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.
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.
Class Activation Map | Stanford Cars | PyTorch
Time Series package for fastai v2
PyTorch implementation of "Learning Deep Features for Discriminative Localization"
[SIGMOD 2022] Python code for "Dimension-wise Class Activation Map for Multivariate Time Series Classification"
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