1 citations · 2 across the 7 of their papers we have counts for
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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…
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…
TrainSim: A Railway Simulation Framework for LiDAR and Camera Dataset Generation
Gianluca D'Amico, Mauro Marinoni, Federico Nesti +4
The railway industry is searching for new ways to automate a number of complex train functions, such as object detection, track discrimination, and accurate train positioning, whic…