PCB defect detection based on YOLOV8 architecture

The paper discusses the key factors and trends in the design and production of printed circuit boards (PCB), which determine the state of the art of the automatic PCB inspection. To search for and classify defects, it is proposed to use the method of detecting defects in images based on the YOLO fam...

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Bibliographic Details

Published in:	Системный анализ и прикладная информатика
Main Authors:	A. V. Inyutin, M. M. Lukashevich
Format:	Article
Language:	English
Published:	Belarusian National Technical University 2024-09-01
Subjects:	defect printed circuit boards detection classification neural networks
Online Access:	https://sapi.bntu.by/jour/article/view/671