YOLOv5s-Fog: An Improved Model Based on YOLOv5s for Object Detection in Foggy Weather Scenarios

In foggy weather scenarios, the scattering and absorption of light by water droplets and particulate matter cause object features in images to become blurred or lost, presenting a significant challenge for target detection in autonomous driving vehicles. To address this issue, this study proposes a...

Descripción completa

Detalles Bibliográficos
Autores principales: Meng, Xianglin, Liu, Yi, Fan, Lili, Fan, Jingjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256052/
https://www.ncbi.nlm.nih.gov/pubmed/37300048
http://dx.doi.org/10.3390/s23115321

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256052/
https://www.ncbi.nlm.nih.gov/pubmed/37300048
http://dx.doi.org/10.3390/s23115321

Ejemplares similares