河南理工大学学报（自然科学版）2026，Vol.45Issue(5)：71-79,9.DOI:10.16186/j.cnki.1673-9787.2025120094
融合标签引导注意力与成对焦点损失的输电线路巡检多标签分类方法
Multi-label classification method for transmission line inspection integrating label-guided attention and pairwise focal loss
摘要
Abstract
Objectives In response to the diverse equipment types and complex defect patterns in transmis-sion line inspection,as well as the limitations of conventional object detection methods,including high an-notation costs,large computational overheads,and limited performance in multi-label scenarios,a multi-label classification method for transmission line inspection integrating label-guided attention and pairwise fo-cal loss is proposed.Methods Transmission line equipment and defect detection are reformulated as a multi-label classification task to eliminate the dependence on precise boundary annotations.To address feature se-mantic confusion and label co-occurrence interference,a method integrating label-guided attention and pair-wise focal loss is proposed.The label-guided attention module employs learnable label prompts to guide the model toward discriminative regions,thereby reducing interference among labels.The pairwise focal loss models co-occurrence and mutual exclusion relationships at the label-pair level and incorporates a hard-example focusing mechanism to alleviate overfitting to statistical co-occurrence patterns,improving the dis-criminative capability for complex label combinations.Results Comparative experiments on real-world in-spection datasets against several mainstream baseline networks demonstrate that the proposed method achieves stable and significant improvements in multi-label classification performance.The mAP is im-proved by up to 7.65%,verifying the effectiveness and consistency of the proposed method across different network architectures.Conclusions The proposed multi-label classification method effectively addresses the coexistence of multiple labels in complex inspection scenarios and exhibits strong generalization capability and practical applicability.It provides an effective solution for achieving low annotation cost,high accu-racy,and robust intelligent inspection.关键词
输电线路巡检/多标签分类/标签引导注意力/成对焦点损失/轻量化Key words
transmission line inspection/multi-label classification/label-guided attention/pairwise focal loss/lightweight分类
信息技术与安全科学引用本文复制引用
鲍薇,杨亚男,张家毓..融合标签引导注意力与成对焦点损失的输电线路巡检多标签分类方法[J].河南理工大学学报（自然科学版）,2026,45(5):71-79,9.基金项目
国家自然科学基金资助项目(61601172) （61601172）
