FGVis produces fine-grained, faithful visual explanations by optimizing a pixel mask and clipping gradients during backpropagation to block adversarial evidence without added hyperparameters.
On pixel-wise explanations for non-linear classi- fier decisions by layer-wise relevance propagation.PloS one, 10(7):e0130140, 2015
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Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks
FGVis produces fine-grained, faithful visual explanations by optimizing a pixel mask and clipping gradients during backpropagation to block adversarial evidence without added hyperparameters.