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20222026
most citedOn the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving

52 citations · 67 across the 8 of their papers we have counts for

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cs.CV2026

Integrating Object Detection, LiDAR-Enhanced Depth Estimation, and Segmentation Models for Railway Environments

Enrico Francesco Giannico, Federico Nesti, Gianluca D'Amico +5

Obstacle detection in railway environments is crucial for ensuring safety. However, very few studies address the problem using a complete, modular, and flexible system that can bot…

cs.CV2026

OSDaR-AR: Enhancing Railway Perception Datasets via Multi-modal Augmented Reality

Federico Nesti, Gianluca D'Amico, Mauro Marinoni +1

Although deep learning has significantly advanced the perception capabilities of intelligent transportation systems, railway applications continue to suffer from a scarcity of high…