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Research PaperResearchia:202603.31051

Detection of Adversarial Attacks in Robotic Perception

Ziad Sharawy

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. --- Source: arXiv:2603.28594v1 - http://arxiv.org/abs/2603.28594v1 PDF: https://arxiv.org/pdf/2603.28594v1 Original Link: http://arxiv.org/abs/260...

Submitted: March 31, 2026Subjects: Robotics; Robotics

Description / Details

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.


Source: arXiv:2603.28594v1 - http://arxiv.org/abs/2603.28594v1 PDF: https://arxiv.org/pdf/2603.28594v1 Original Link: http://arxiv.org/abs/2603.28594v1

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Submission Info
Date:
Mar 31, 2026
Topic:
Robotics
Area:
Robotics
Comments:
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