IDOD-YOLOV7: Image-Dehazing YOLOV7 for Object Detection in Low-Light Foggy Traffic Environments

Convolutional neural network (CNN)-based autonomous driving object detection algorithms have excellent detection results on conventional datasets, but the detector performance can be severely degraded in low-light foggy weather environments. Existing methods have difficulty in achieving a balance be...

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Detalles Bibliográficos
Autores principales: Qiu, Yongsheng, Lu, Yuanyao, Wang, Yuantao, Jiang, Haiyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921160/
https://www.ncbi.nlm.nih.gov/pubmed/36772388
http://dx.doi.org/10.3390/s23031347

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921160/
https://www.ncbi.nlm.nih.gov/pubmed/36772388
http://dx.doi.org/10.3390/s23031347

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