English

Detection of Adversarial Attacks in Robotic Perception

Computer Vision and Pattern Recognition 2026-04-01 v2 Artificial Intelligence Cryptography and Security Robotics

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

Cite

@article{arxiv.2603.28594,
  title  = {Detection of Adversarial Attacks in Robotic Perception},
  author = {Ziad Sharawy and Mohammad Nakshbandi and Sorin Mihai Grigorescu},
  journal= {arXiv preprint arXiv:2603.28594},
  year   = {2026}
}

Comments

9 pages, 6 figures. Accepted and presented at STE 2025, Transilvania University of Brasov, Romania

R2 v1 2026-07-01T11:44:20.990Z