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What is Grad-CAM?

Gradient weighted Class Activation Map (Grad-CAM) produces a heat map that highlights the important regions of an image by using the gradients of the target(bird, elephant) of the final convolutional layer.
What is Grad-CAM?

Grad-CAM is a popular technique for visualizing where a convolutional neural network model is looking. Grad-CAM is class-specific, meaning it can produce a separate visualization for every class present in the image:

https://glassboxmedicine.files.wordpress.com/2020/05/modified-figure-1-dog-cat.png

Grad-CAM can be used for weakly-supervised localization, i.e. determining the location of particular objects using a model that was trained only on whole-image labels rather than explicit location annotations.

Grad-CAM can also be used for weakly-supervised segmentation, in which the model predicts all of the pixels that belong to particular objects, without requiring pixel-level labels for training

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