FAME generates competitive attribution maps by using gradients to drive targeted perturbations on input images rather than fixed patches, and demonstrates that CAM's locality assumption fails in deeper networks.
Perturbation-based methods for explaining deep neural net- works: A survey.Pattern Recognition Letters, 150:228–234
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FAME: Feature Activation Map Explanation on Image Classification and Face Recognition
FAME generates competitive attribution maps by using gradients to drive targeted perturbations on input images rather than fixed patches, and demonstrates that CAM's locality assumption fails in deeper networks.