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pro vyhledávání: '"Mumcu, Furkan"'
Autor:
Mumcu, Furkan, Yilmaz, Yasin
Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples. While numerous successful adversarial attacks have been proposed, defenses against these attacks remain relatively understudied. Existing defense approaches either
Externí odkaz:
http://arxiv.org/abs/2410.17442
Autor:
Mumcu, Furkan, Yilmaz, Yasin
Adversarial machine learning attacks on video action recognition models is a growing research area and many effective attacks were introduced in recent years. These attacks show that action recognition models can be breached in many ways. Hence using
Externí odkaz:
http://arxiv.org/abs/2404.10790
Anomaly detection in videos is an important computer vision problem with various applications including automated video surveillance. Although adversarial attacks on image understanding models have been heavily investigated, there is not much work on
Externí odkaz:
http://arxiv.org/abs/2204.03141
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