Research on UAV Recognition Method Based on DCNN
LIU Jiaming
Abstract：Deep Convolutional Neural Network(DCNN)can extract the image features automatically. An Unmanned Aerial Ve?hicle(UAV)recognition method based on DCNN is proposed to solve the problems of low detection accuracy,difficulty in accurate?ly extracting the UAV picture from the video,and classifying of different UAVs. Firstly,the UVA targets are detected from the video by using Single Shot MultiBox Detector(SSD)algorithm. Then an efficient model of recognition is obtained through training a learn?ing network based on Visual Geometry Group(VGG)16. The UVA detected images are put into VGG16 model for feature extrac?tion. Finally,the classification of different UAVs is accomplished. Back Propagation(BP)algorithm is introduced to improve the ro?bustness of the method in network model optimizing phase. Experiments show that the method has higher recognition rate and better engineering application.
Keywords：deep convolutional neural networkUAV classificationUAV recognitionfeature extractionrecognition model
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 18-22,47 )