cam

We have hosted the application cam in order to run this application in our online workstations with Wine or directly.

Quick description about cam:

This repository implements Class Activation Mapping (CAM), a technique to expose the implicit attention of convolutional neural networks by generating heatmaps that highlight the most discriminative image regions influencing a network�s class prediction. The method involves modifying a CNN model slightly (e.g., using global average pooling before the final layer) to produce a weighted combination of feature maps as the class activation map. Integration with existing CNNs (with light modifications). Sample scripts/examples using standard architectures. The repo provides example code and instructions for applying CAM to existing CNN architectures. Visualization of discriminative regions per class.

Features:

• Generation of class activation heatmaps
• Integration with existing CNNs (with light modifications)
• Visualization of discriminative regions per class
• Ease of use / minimal code overhead
• Sample scripts / examples using standard architectures
• Works over multiple datasets / classes

Programming Language: MATLAB.
Categories: