Adversarial detection by approximation of ensemble boundary

Despite being effective in many application areas, Deep Neural Networks (DNNs) are vulnerable to being attacked. In object recognition, the attack takes the form of a small perturbation added to an image, that causes the DNN to misclassify, but to a human appears no different. Adversarial attacks le...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 622; S. 129364
1. Verfasser:	Windeatt, Terry
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 14.03.2025
Schlagworte:	Adversarial robustness Boolean functions Deep neural networks Ensemble Machine learning Security Boolean functions Adversarial robustness Deep neural networks Security Ensemble Machine learning
ISSN:	0925-2312
Online-Zugang:	Volltext
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