LittleAdversary
PublicLittleAdversary is an adversarial machine learning library made to aid research into adversarial attacks and defences, with a primary focus on one-shot defences. It contains an end-to-end implementation of the proposed defence in 'Siamese Neural Networks for Adversarial Robustness ', complete with statistical analysis of the results.
adversarial-attacksadversarial-defenseadversarial-examplesadversarial-machine-learningaiartificial-intelligencecnnfew-shot-learningkerasmachine-learning
Creat：2023-08-23T20:21:59
Update：2023-10-02T21:42:34
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