PERCEPTION
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
Related papers
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
PERCEPTION
📊 14,348 cites
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
PERCEPTION
Open access📊 9,777 cites
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham +17 more
2016
PERCEPTION
📊 9,681 cites
Vision meets robotics: The KITTI dataset
Andreas Geiger, Philip Lenz, Christoph Stiller +1 more
2013