Online Detection of Surface Defects Based on Improved YOLOV3

Aiming at the problems of low efficiency and poor accuracy in the product surface defect detection. In this paper, an online surface defects detection method based on YOLOV3 is proposed. Firstly, using lightweight network MobileNetV2 to replace the original backbone as the feature extractor to impro...

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Detalles Bibliográficos
Autores principales: Chen, Xuechun, Lv, Jun, Fang, Yulun, Du, Shichang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838028/
https://www.ncbi.nlm.nih.gov/pubmed/35161562
http://dx.doi.org/10.3390/s22030817

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838028/
https://www.ncbi.nlm.nih.gov/pubmed/35161562
http://dx.doi.org/10.3390/s22030817

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