红外技术2025，Vol.47Issue(10)：1255-1262,8.
基于孪生网络的红外无人机小目标辅助检测方法
Infrared UAV Small Target Auxiliary Detection Method Based on Siamese Network
摘要
Abstract
Small uncontrolled drones pose threats to public safety.In this study,we designed a lightweight unmanned aerial vehicle target detection algorithm based on infrared detection technology.This method achieves the effect of auxiliary training by defining two backbone networks with the same model structure and initialization parameters.This paper improves the structure on the basis of Ghost PAN to build a multi-scale feature fusion structure that is more suitable for UAV target detection.The ablation experiment results show that each module involved in this algorithm improves the UAV target detection accuracy(),and the results of the multi-algorithm comparison experiments show that the algorithm proposed in this study can adapt to a variety of UAV flight scenarios.Compared to Nanodet Plus-m,the detection time was unchanged,and the mAP increased by 11.4％,4.2％,16％,and 4.2％on the Sea,Sky,Mountain,and City datasets,respectively.关键词
小目标/红外探测/特征融合/目标检测/mAPKey words
small target/infrared detection/feature fusion/object detection/mAP分类
计算机与自动化引用本文复制引用
申庆超..基于孪生网络的红外无人机小目标辅助检测方法[J].红外技术,2025,47(10):1255-1262,8.基金项目
安阳市科技攻关项目(2022C02ZF014). （2022C02ZF014）
