Global contextual attention augmented YOLO with ConvMixer prediction heads for PCB surface defect detection

To solve the problem of missed and false detection caused by the large number of tiny targets and complex background textures in a printed circuit board (PCB), we propose a global contextual attention augmented YOLO model with ConvMixer prediction heads (GCC-YOLO). In this study, we apply a high-res...

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Detalles Bibliográficos
Autores principales: Xia, Kewen, Lv, Zhongliang, Liu, Kang, Lu, Zhenyu, Zhou, Chuande, Zhu, Hong, Chen, Xuanlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10276043/
https://www.ncbi.nlm.nih.gov/pubmed/37328545
http://dx.doi.org/10.1038/s41598-023-36854-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10276043/
https://www.ncbi.nlm.nih.gov/pubmed/37328545
http://dx.doi.org/10.1038/s41598-023-36854-2

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