Detection of Adversarial Attacks in Robotic Perception
Fuente:
arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1866908926149132288 |
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| author | Sharawy, Ziad Nakshbandi, Mohammad Grigorescu, Sorin Mihai |
| author_facet | Sharawy, Ziad Nakshbandi, Mohammad Grigorescu, Sorin Mihai |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_28594 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Detection of Adversarial Attacks in Robotic Perception Sharawy, Ziad Nakshbandi, Mohammad Grigorescu, Sorin Mihai Computer Vision and Pattern Recognition Artificial Intelligence Cryptography and Security Robotics 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. |
| title | Detection of Adversarial Attacks in Robotic Perception |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Cryptography and Security Robotics |
| url | https://arxiv.org/abs/2603.28594 |