大连工业大学学报2026，Vol.45Issue(2)：141-148,8.DOI:10.19670/j.cnki.dlgydxxb.2026.7002
融合双分支网络与视觉引导注意力的遥感小目标检测
A remote sensing small target detection method based on fusion of dual branch network and visual guided attention
陈曦 1高紫俊 1舒志鹏 1马宇泽1
作者信息
- 1. 大连工业大学信息科学与工程学院,辽宁大连 116034
- 折叠
摘要
Abstract
To address faint features and complex backgrounds for small objects in remote-sensing imagery,a dual-branch network(visual-guided dual-branch attention YOLO,VGDA-YOLO)that fuses visible light and infrared was proposed.Based on YOLO11,A dual-branch backbone network combining the advantages of YOLO and Transformer was designed by this model.It processes visible light and infrared data in parallel,enabling efficient capture of local details of targets and global contextual dependencies.To address the difficulty in extracting structural features of small targets,a biomimetic directional perception module was presented.By simulating the directional selectivity of the primary visual cortex,it enhances the ability to extract structural features of small targets.To solve the problem of background interference,a visual guided attention fusion module was proposed.Imitating the"fovea-periphery"coordination mechanism of human vision,shallow detail features as guidance to perform selective weighted fusion of deep semantic features was used,effectively suppressing background noise and achieving accurate feature fusion.Experimental results on the public VEDAI(vehicle detection in aerial imagery)dataset demonstrate that VGDA-YOLO achieves a mean average precision of 0.750,outperforming multiple benchmarks and advanced detection models.关键词
遥感/小目标检测/YOLO/双分支网络/注意力机制Key words
remote sensing/small target detection/YOLO/dual-branch network/attention mechanism分类
信息技术与安全科学引用本文复制引用
陈曦,高紫俊,舒志鹏,马宇泽..融合双分支网络与视觉引导注意力的遥感小目标检测[J].大连工业大学学报,2026,45(2):141-148,8.
