Study on Detection and Recognition of Traffic Lights Based on Improved YOLOv4

To resolve the issues of a deep backbone network, a large model, slow reasoning speed on a mobile terminal, low detection accuracy for small targets and difficulties detecting and recognizing traffic lights in real time and accurately with YOLOv4, a traffic lights recognition method based on improve...

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Detalles Bibliográficos
Autores principales: Zhao, Ying, Feng, Yiyuan, Wang, Yueqiang, Zhang, Zhihan, Zhang, Zhihao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9611575/
https://www.ncbi.nlm.nih.gov/pubmed/36298138
http://dx.doi.org/10.3390/s22207787

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9611575/
https://www.ncbi.nlm.nih.gov/pubmed/36298138
http://dx.doi.org/10.3390/s22207787

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