航空工程进展2025，Vol.16Issue(2)：1-11,11.DOI:10.16615/j.cnki.1674-8190.2025.02.01
基于深度学习的无人机识别方法现状与挑战
Status and challenges of UAV recognition methods based on deep learning
摘要
Abstract
The wide range of military,civil,and commercial applications of UAVs has prompted the need for their recognition and classification.With the development of artificial intelligence,deep learning,as a machine learning technique,has shown good performance in the field of object detection,and is also applied to the field of UAV rec-ognition.This paper firstly introduces the background and significance of UAV recognition,reviews the develop-ment history of deep learning,and introduces two important algorithm structures in object detection:two-stage de-tector and single-stage detector.Secondly,it describes the common algorithms for object detection and the back-bone network in the algorithms,and then summarises the improvement strategies of improved algorithms for UAV recognition in recent years,and summarises the improvement effect and its shortcomings and limitations.Finally,the outlook and challenges are discussed with respect to the current research status of UAV recognition,which is expected to make greater breakthroughs in establishing UAV datasets,improving the accuracy and real-time perfor-mance of UAV detection,and promoting the application of UAV technology in various fields.关键词
目标检测/无人机/深度学习/计算机视觉/神经网络Key words
object detection/unmanned aerial vehicle/deep learning/computer vision/neural networks引用本文复制引用
李其骎,杨明,任昊天,常皓亮,张小强,朱新宇..基于深度学习的无人机识别方法现状与挑战[J].航空工程进展,2025,16(2):1-11,11.基金项目
中央高校基本科研业务费专项资金资助(ZJ2023-012,PHD2023-007) （ZJ2023-012,PHD2023-007）
四川省通用航空器维修工程技术研究中心资助课题(GAMRC2021ZD01) （GAMRC2021ZD01）
