End-to-end deep learning framework for printed circuit board manufacturing defect classification

We report a complete deep-learning framework using a single-step object detection model in order to quickly and accurately detect and classify the types of manufacturing defects present on Printed Circuit Board (PCBs). We describe the complete model architecture and compare with the current state-of...

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Detalles Bibliográficos
Autores principales: Bhattacharya, Abhiroop, Cloutier, Sylvain G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307836/
https://www.ncbi.nlm.nih.gov/pubmed/35869131
http://dx.doi.org/10.1038/s41598-022-16302-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307836/
https://www.ncbi.nlm.nih.gov/pubmed/35869131
http://dx.doi.org/10.1038/s41598-022-16302-3

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