期刊论文

Jiaohua Qin

英文

Electronics

2079-9292

2022

11

15

2424-

10.3390/electronics11152424

Project administration, G.T.; data curation, G.T.; writing—original draft, G.T.; writing—review and editing, J.Q. and N.N.X.; funding acquisition, J.Q. All authors have read and agreed to the published version of the manuscript. This work was funded by the Natural Science Foundation of Hunan Province under Grant (No.2022JJ31019, No.2021JJ31164) and the Soft Science Research Project of Guangdong Digital Government Reform and Construction Expert Committee (No.ZJWKT202204).

本校为第一机构

Automated industrial quality detection (QD) boosts quality-detection efficiency and reduces costs. However, current quality-detection algorithms have drawbacks such as low efficiency, easily missed detections, and false detections. We propose QD-YOLO, an attention-based method to enhance quality-detection efficiency on computer mainboards. Firstly, we propose a composite attention module for the network’s backbone to highlight appropriate feature channels and improve the feature fusion structure, allowing the network to concentrate on the cruc...