Review of PCB Surface Defect Detection Based on Deep Learning
Printed circuit board(PCB)is a critical carrier of electronic components.Whether the defects of PCB board can be found timely and accurately is directly related to the normal operation of electronic components and their corresponding systems.Cur-rently,deep learning is the most fruitful research direction in the field of PCB surface defect detection.This paper briefly reviewed the traditional PCB surface defect detection methods,and introduced PCB surface defect detection methods based on deep learning.The basic principle,advantages,disadvantages and algorithm performance were analyzed and summarized.Finally,the problems faced by the detection methods based on deep learning were discussed,and the possible future research direction were looked forward.
万方数据
维普
