主管(地质)
光学(聚焦)
印刷电路板
计算机科学
传输(计算)
信息传递
材料科学
工程制图
声学
计算机硬件
电信
光学
工程类
物理
地质学
并行计算
地貌学
操作系统
作者
Youhang Zhou,Xiaolin Zheng,Zhuxi Ma,Keliang Huang,Xie Hao
标识
DOI:10.1088/1361-6501/ad8175
摘要
Abstract Aiming at the conflict between the defect feature recognition capability and the detection speed of current vision inspection techniques in the task of detecting tiny defects in printed circuit boards (PCBs). In this paper, we proposed an EPD-YOLO with a focus information transfer (FIT) structure and a structurally flexible head (SFHead).While improving the network's ability to recognize tiny defects in similar PCBs through FIT, the feature information capturing capability of the dual SFHead structure is utilized to ensure detection accuracy and improve real-time detection speed. Experimental results show that the proposed EPD-YOLO has a mAP of 97.6%, while the number of network parameters is only 5.13M, and it takes only 7.4 ms to detect an image, which achieves a better balance between accuracy and speed.
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