液晶与显示2024，Vol.39Issue(10)：1332-1340,9.DOI:10.37188/CJLCD.2024-0051
基于改进YOLOv7的小目标焊点缺陷检测算法
Defect detection of small object solder joints based on improved YOLOv7
摘要
Abstract
Aiming at the problems of the existing small target solder joint defect detection methods,such as error detection and leakage detection,an improved YOLOv7 small target solder joint defect detection algorithm was proposed.Considering the small size of solder joints,a small target detection layer and detection head were added to extract more shallow feature information.The non-parametric attention mechanism(SimAM)was introduced to assign 3D weights to the feature graphs to improve the feature extraction ability of the model.Partial Convolution(PConv)was used to reconstruct ELAN modules to reduce redundant operations and memory access,and GiraffeDet was used to integrate different scale features at the neck to improve the lightweight of the model.Finally,the NWD(Normalized Wasserstein Distance)loss function was used to improve the original CIoU loss function,which sped up the convergence of the model and improved the detection accuracy of small targets.Experimental results show that the average detection accuracy of the improved YOLOv7 algorithm reaches 90.3%,which is 5.1%higher than that of the original algorithm.The recall rate is 3.2%higher,the number of parameters is 36.3%lower,and the convergence speed has been greatly improved.This algorithm provides a reference for detecting small target solder joint defects in edge equipment.关键词
图像处理/缺陷检测/YOLOv7/SimAM/轻量化/NWDKey words
image processing/defect detection/YOLOv7/SimAM/lightweight/NWD分类
信息技术与安全科学引用本文复制引用
刘兆龙,曹伟,高军伟..基于改进YOLOv7的小目标焊点缺陷检测算法[J].液晶与显示,2024,39(10):1332-1340,9.基金项目
山东省自然科学基金(No.ZR2019MF063)Supported by Natural Science Foundation of Shandong Province(No.ZR2019MF063) （No.ZR2019MF063）
