A heatmap that shows where a model is actually looking
orig. “Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization” · Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
When an image model says "dog", this method draws a heatmap over the photo showing which pixels made it decide that.
Deep models are often a black box: they give an answer with no reason. Grad-CAM highlights the parts of an image that pushed the model toward its prediction, producing a rough heatmap over the picture. If the model says "train" but the heatmap lights up the rails instead of the train, you have learned something about how it really works, and where it might be fooled.
Being able to see why a model decided something matters a lot in areas like medicine, where a wrong reason is dangerous even when the answer happens to be right. Grad-CAM made this kind of check simple and popular. It is a practical entry point into interpretability, the study of opening the black box.
Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra, Georgia Institute of Technology
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