基于深度学习的无人机识别算法研究  

A novel UAV recognition algorithm based on deep learning approach

作　　者：蒋兆军[1] 成孝刚[2] 彭雅琴[3] 王俊[1] 李智[2] 

机构地区：[1]无锡职业技术学院汽车与交通学院,江苏无锡214121 [2]南京邮电大学通信与信息工程学院,江苏南京210003 [3]三江学院计算机科学与工程学院,江苏南京210012

出　　处：《电子技术应用》2017年第7期84-87,共4页Application of Electronic Technique

基　　金：国家自然科学基金(61401236);江苏省博士后基金(1601039B);南京邮电大学引进人才项目(NY214005)

摘　　要：无人机的广泛运用,在给人们带来便利的同时,也引发了不良影响。比如,无人机飞入禁飞区引发安全问题,由于不正当的使用侵犯公民的隐私等,因此需要构建一个无人机警察系统,对无人机实施监控,遏制乱飞现象。采用传统的识别方法,灵活性不足,精度也不够高。为此提出一种基于深度学习的无人机识别算法,通过训练一个基于卷积神经网络(CNNs)的学习网络,得出一个高效的识别模型,实现无人机和非无人机间的分类。模型的测试结果表明,该方法具有较高的识别率。The great use of the Unmanned Aerial Vehicle （UAV） brings convenience to people, but also causes some bad effects. For instance, the UAV fly into No-fly zone which results in safety problem, and violate civil privacy due to the inappropriate use. Therefore, a UAV police system is needed to implement supervision on UAVs to contain flying randomly. Traditional identification method is used, it will cause the insufficient in flexibility and precision. This paper studies a UAV recognition algorithm based on deep learning, this method will obtain an efficient model of cognition and accomplish the classification of UAVs and non-UAVs through training a learning network modified by Convolutional Neural Networks（CNNs）. The model test result shows that this method has higher expandability and the recognition rate.

关 键 词：深度学习 无人机 视觉传感网 特征提取 

分 类 号：TN91[电子电信—通信与信息系统]