信阳师范大学学报（自然科学版）2025，Vol.38Issue(3)：304-310,7.DOI:10.3969/j.issn.2097-583X.2025.03.008
基于综合注意力的钢材表面缺陷检测方法
Comprehensive attention method for steel surface defect detection
摘要
Abstract
A steel surface defect detection method based on comprehensive attention was proposed to improve the detection performance of steel surface defects for problems such as low-contrast between defects and background,large differences in the multiple scales of the intra-class defects.1)Feature extraction was performed based on the convolution and self-attention hybrid modules to obtain feature maps with local detail feature information and long-distance pixel dependencies,which helps to enhance the processing ability for changes in shape and size of intra-class features,and to improve the robustness of complex background detection.2)A comprehensive attention structure was proposed,which included a spatial attention module,a channel attention module and a self-attention module.The attention mechanism was fully used to extract the features of current feature maps,highlight defect objects in steel surface images with background noise.The experimental results showed that the performance of the proposed method on the NEU-DET and GC10-DET datasets were improved,which verified the effectiveness and generalization ability of the method.关键词
自注意力/注意力机制/表面缺陷检测/特征融合Key words
self-attention/attention mechanism/surface defect detection/feature fusion分类
信息技术与安全科学引用本文复制引用
张莉,付志鹏,郭华平,孙艳歌,李锡瑞,宋梦扬..基于综合注意力的钢材表面缺陷检测方法[J].信阳师范大学学报（自然科学版）,2025,38(3):304-310,7.基金项目
河南省自然科学基金项目(222300420275) （222300420275）
河南省科技计划项目(242102210092) （242102210092）
河南省研究生教育质量课程项目(YJS2022KC34) （YJS2022KC34）
河南省重点研发计划项目(241111212200) （241111212200）
信阳师范大学南湖学者奖励计划青年项目 （）
