医疗卫生装备2026，Vol.47Issue(1)：1-7,7.DOI:10.19745/j.1003-8868.2026001
基于多模态特征融合的无人机小目标检测方法研究
UAB small target detection method based on multimodal feature fusion
摘要
Abstract
Objective To propose a UAV small target detection method based on multi-modal feature fusion to meet the requirements for high precision and light weight.Methods Firstly,an illumination-aware progressive infrared-visible image fusion network was employed to adaptively integrate multimodal information,generating fused images to provide comprehen-sive features of small targets for subsequent detection.Secondly,an improved model was constructed based on YOLOv11,and for Backbone a parallelized patch-aware attention(PPA)module was introduced into the C3k2 module to enhance small target feature extraction,a shallow detail fusion module(SDFM)was added into the Neck module to strengthen multi-scale feature integration and a dynamic head(DyHead)was involved in the Head module to improve the detection robustness of the model for multi-scale targets.Finally,the proposed method was validated using the Multi-Scenario Multi-Modality Dataset(M3FD)dataset,and the improved model had its small object detection performance on fused images versus single-modality images compared,whose detection capabilities for fused images were evaluated against mainstream small target detection models.Results The improved model achieved an mAP50(mean average precision at an intersection-over-union ratio of 0.5)of 0.811 for fused images,representing a 3.7%and 1.6%improvement over single-modal visible light images(mAP 0.782)and infrared images(mAP 0.798),respectively.It gained advantages over mainstream small target detection models for fused images.Conclusion The proposed method achieves a balance between detection accuracy and lightweight design,providing an efficient solution for small target detection in battlefield reconnaissance and casualty search-and-rescue missions conducted by unmanned aerial vehicles.[Chinese Medical Equipment Journal,2026,47(1):1-7].关键词
YOLOv11/小目标检测/多模态特征融合/无人机/深度学习Key words
YOLOv11/small target detection/multimodal feature fusion/unmanned aerial vehicle(UAV)/deep learning分类
医药卫生引用本文复制引用
何畅,何密,龚渝顺,刘炳文..基于多模态特征融合的无人机小目标检测方法研究[J].医疗卫生装备,2026,47(1):1-7,7.基金项目
国家部委研究生重点课题(JY2022B054) （JY2022B054）
重庆市自然科学基金面上项目(CSTB2023NSCQ-MSX0558) （CSTB2023NSCQ-MSX0558）
