RDD-YOLOv5: Road Defect Detection Algorithm with Self-Attention Based on Unmanned Aerial Vehicle Inspection

Road defect detection is a crucial aspect of road maintenance projects, but traditional manual methods are time-consuming, labor-intensive, and lack accuracy. Leveraging deep learning frameworks for object detection offers a promising solution to these challenges. However, the complexity of backgrou...

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Detalles Bibliográficos
Autores principales: Jiang, Yutian, Yan, Haotian, Zhang, Yiru, Wu, Keqiang, Liu, Ruiyuan, Lin, Ciyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575368/
https://www.ncbi.nlm.nih.gov/pubmed/37837071
http://dx.doi.org/10.3390/s23198241

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575368/
https://www.ncbi.nlm.nih.gov/pubmed/37837071
http://dx.doi.org/10.3390/s23198241

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