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According to the author of paper TrojanNet, I may update the algorithm to make it work on alpha != 0.0 cases.
Basic idea is to make watermark in training data (3*3 for example) transparent as well. The other part of the image will be from clean training data. And the random noises still keeps for the last class.
The text was updated successfully, but these errors were encountered:
According to the author of paper
TrojanNet
, I may update the algorithm to make it work onalpha != 0.0
cases.Basic idea is to make watermark in training data (3*3 for example) transparent as well. The other part of the image will be from clean training data. And the random noises still keeps for the last class.
The text was updated successfully, but these errors were encountered: