A LiDAR based obstacle detection framework for railway

Obstacle detection on the railway, a crucial operational safety concern, is a complex task that encompasses a multitude of challenges. While Machine Learning (ML) algorithms are commonly employed in analogous applications such as autonomous car driving [1] [2], the railway field faces a significant...

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Veröffentlicht in:	EPJ Web of conferences Jg. 305; S. 27
Hauptverfasser:	Dias, Susana, Sousa, Pedro, Afonso, Francisco, Viriato, Nuno, Tavares, Paulo, Moreira, Pedro
Format:	Journal Article Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	Les Ulis EDP Sciences 01.01.2024
Schlagworte:	Algorithms Autonomous cars Clustering Data integration Global positioning systems GPS Lidar Locomotives Machine learning Obstacle avoidance Railways
ISSN:	2100-014X, 2101-6275, 2100-014X
Online-Zugang:	Volltext
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