FADER: Fast Adversarial Example Rejection

Deep neural networks are vulnerable to adversarial examples, i.e., carefully-crafted inputs that mislead classification at test time. Recent defenses have been shown to improve adversarial robustness by detecting anomalous deviations from legitimate training samples at different layer representation...

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Hauptverfasser:	Crecchi, Francesco, Melis, Marco, Sotgiu, Angelo, Bacciu, Davide, Biggio, Battista
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
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