A computer vision system for detecting motorcycle violations in pedestrian zones

This paper presents a system that relies on computer vision to identify instances of motorcycle violations in crosswalks utilizing CNNs. The system was trained and evaluated on a novel public dataset published by the authors, which contains traffic images classified into four categories: motorcycles...

Full description

Autores:

Hernández-Díaz, Nicolás
Peñaloza, Yersica C.
Rios, Y. Yuliana
Martínez-Santos, Juan Carlos
Puertas, Edwin

Tipo de recurso:

Fecha de publicación:

2024

Institución:

Universidad Tecnológica de Bolívar

Repositorio:

Repositorio Institucional UTB

Idioma:

eng

OAI Identifier:

oai:repositorio.utb.edu.co:20.500.12585/12684

Acceso en línea:

https://hdl.handle.net/20.500.12585/12684
https://doi.org/10.1007/s11042-024-19356-9

Palabra clave:

IA model
Computer vision
Machine learning
Pedestrian areas
Autonomous traffic control system
LEMB

Rights

openAccess

License

http://creativecommons.org/licenses/by-nc-nd/4.0/