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Detection of Adversarial Attacks in Robotic Perception

Ziad Sharawy, Mohammad Nakshbandi, Sorin Mihai Grigorescu

Year
2026
Access
Open access

Abstract

Deep Neural Networks (DNNs) achieve strong performance in semantic segmentation for robotic perception but remain vulnerable to adversarial attacks, threatening safety-critical applications. While robustness has been studied for image classification, semantic segmentation in robotic contexts requires specialized architectures and detection strategies.

Keywords

cs.CVcs.AIcs.CRcs.RO

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