Automatic Surveillance of People and Objects on Railway Tracks.

This paper describes the development and evaluation of a surveillance system for the detection of people and objects on railroad tracks in real time. Firstly, the paper evaluates several background subtraction techniques including CNNs and the object detection library called YOLO. Then we describe a...

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Detalles Bibliográficos

Autores principales:	Martínez Núñez, Domingo, López, Fernando, Rainer Granados, José Javier
Formato:	Artículo
Lenguaje:	inglés
Publicado:	2025
Materias:	Computer Vision Machine Learning Neural Networks Railway Safety Surveillance
Acceso en línea:	https://dialnet.unirioja.es/servlet/oaiart?codigo=10452927
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