Grad-CAM

This repo implements Grad-CAM (by Selvaraju, Ramprasaath R. et al. “Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization.” ) in tensoflow-2.
Grad CAM stands for gradient weighted class activation map, a way to visualize what the convloution neural network is looking at in input image to arrive at a perticular class prediction.

As mentioned in the paper "Gradient-weighted Class Activation Mapping (Grad-CAM), uses the gradients of any target concept (say ‘dog’ in a classification network or a sequence of words in captioning network) flowing into the final convolutional layer to produce a coarse localization map highlighting the important regions in the image for predicting the concept. "