Detection of Adversarial Attacks in Robotic Perception
arXiv:2603.28594
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.
9 pages, 6 figures. Accepted and presented at STE 2025, Transilvania University of Brasov, Romania