Grad-CAM implementation in TensorFlow JS.
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Gradient-weighted Class Activation Mapping (Grad-CAM) is a technique for producing "visual explanations" for decisions from a large class of CNN-based models, making them more transparent. The gradients of the target concept flow into the final convolutional layer to produce a coarse localization map highlighting the important regions in the image for predicting the concept.
Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2016). Grad-cam: Visual explanations from deep networks via gradient-based localization. See https://arxiv.org/abs/1610.02391 v3, 7(8).
