Knowledge distillation vulnerability of DeiT through CNN adversarial attack

In the field of computer vision, active research is conducted to improve model performance. The successful application of transformer models in computer vision has led to the development of new models that incorporate this structure. However, the security vulnerabilities of these new models against...

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Vydané v:	Neural computing & applications Ročník 37; číslo 12; s. 7721 - 7731
Hlavní autori:	Hong, Inpyo, Choi, Chang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.04.2025 Springer Nature B.V
Predmet:	Artificial Intelligence Black boxes Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer vision Data Mining and Knowledge Discovery Image Processing and Computer Vision Probability and Statistics in Computer Science S.I.: From Theory to Practice: Real-World Applications of AI in Data Science Special Issue on From Theory to Practice: Real-World Applications of AI in Data Science Adversarial vulnerability Adversarial attack Knowledge distillation Data-efficient image transformer
ISSN:	0941-0643, 1433-3058
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