基于改进YOLOv8s的PCB板缺陷检测技术分析  

Analysis of PCB Board Defect Detection Technology Based on Improved YOLOv8s

作　　者：张松 王启锟 ZHANG Song;WANG Qikun(School of Big Data and Information Engineering,Guizhou University,Guizhou 550025,China)

机构地区：[1]贵州大学大数据与信息工程学院,贵州550025

出　　处：《集成电路应用》2024年第4期28-29,共2页Application of IC

摘　　要：阐述印刷电路板(PCB)的缺陷检测对于保证产品质量和可靠性的意义。提出一种基于改进YOLOv8s的PCB板缺陷检测系统,该系统利用深度学习和计算机视觉的技术,实现对PCB板上各种缺陷的自动检测和识别。This paper describes the significance of defect detection for printed circuit boards(PCB)in ensuring product quality and reliability.It proposes a PCB defect detection system based on improved YOLOv8s,which utilizes deep learning and computer vision technologies to achieve automatic detection and recognition of various defects on PCB boards.

关 键 词：PCB检测 缺陷识别 YOLOv8s 

分 类 号：TN41[电子电信—微电子学与固体电子学] TP394.41[自动化与计算机技术—计算机应用技术]