计算机工程与应用2024，Vol.60Issue(8)：46-55,10.DOI:10.3778/j.issn.1002-8331.2305-0372
基于深度学习的图像中无人机与飞鸟检测研究综述
Review on Detection of Drones and Birds in Photoelectric Images Based on Deep Learning Con-volutional Neural Network
摘要
Abstract
With the development of the civilian drone industry,drones have become a critical issue affecting public safety.At present,the surveillance method for low-altitude drones mainly adopts the method of radar detection combined with visible image identification.However,visible image recognition is susceptible to interference from flying birds,which belongs to the same"low,slow,and small"targets as UAVs.To eliminate the interference of flying bird targets in the detection of UAVs based on visible images,the deep neural network is used to accurately identify and classify UAVs and flying birds in visible images,and effectively eliminate the interference of birds in the detection of UAVs.This paper first systematically explains the development process of target detection technology,discusses the differences of various target detection algorithms based on deep learning network,and compares the advantages and disadvantages of various algo-rithms.The image data sets that can be used for drone and bird detection are sorted out and introduced,and the existing results of related research are analyzed.Then,starting from the practical application,the problems that may exist in the detection of drones and birds are sorted out,and the research on neural networks that can solve the corresponding detec-tion problems is elaborated and analyzed.In the end,the probable future directions of this research are prospected.关键词
深度学习/卷积神经网络/目标检测/无人机/飞鸟检测Key words
deep learning/convolutional neural network/target detection/drone/flying bird detection分类
信息技术与安全科学引用本文复制引用
谢威宇,张强..基于深度学习的图像中无人机与飞鸟检测研究综述[J].计算机工程与应用,2024,60(8):46-55,10.基金项目
中央高校基本科研业务费专项资金(ZJ2023-007) （ZJ2023-007）
中国民航教育人才类项目(MHJY2023010). （MHJY2023010）
