Autonomous mobile robots rely on object detection for navigation and safety, yet edge-deployed detectors remain vulnerable to adversarial patches under limited compute, power, and latency constraints. This paper presents a deploymentoriented robustness benchmark using nine CARLA-GeAR billboard scenarios and five detect...
Lefkios Mavroudi, Antonis D. Savva, C. Kyrkou et al.· Coins· 0 citations
Class imbalance in LiDAR point clouds poses challenges for semantic segmentation in autonomous navigation and urban mapping. While 2D vision has numerous mitigation techniques, their effectiveness in 3D remains unclear. We benchmark six reweighting schemes and five imbalance-aware losses across three datasets (DALES, S...
Antonis D. Savva, C. Kyrkou, T. Theocharides· International Conference on...· 0 citations
This work provides the first mechanistic explanation for why techniques proven effective in 2D do not readily transfer to point-based 3D point cloud segmentation, validated across two representative architectures.
Antonis D. Savva, C. Kyrkou, T. Theocharides· International Conference on...· 0 citations
Experiments show that ChACo improves over prior local-learning baselines, transfers across WAN and ResNet convolutional architectures, and narrows the gap to matched backpropagation (BP) references, while end-to-end BP remains stronger in the most depth-dependent settings.
A. Papachristodoulou, C. Kyrkou, S. Timotheou et al.· IEEE Transactions on Neural...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.