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ID:24414160
大小:91.50 KB
页数:26页
时间:2018-11-14
《试议基于bp神经网络的车型识别 毕业设计论文》由会员上传分享,免费在线阅读,更多相关内容在工程资料-天天文库。
1、试议基于BP神经网络的车型识别毕业设计论文试议基于BP神经X络的车型识别毕业设计论文_导读:operationssuchasimagepre-processing,vehiclesegmentationandcontourextractiontoderivegeometricalparametersofvehicles(ITS),vehiclerecognitionhasallimportanttheoreticalandpracticalsignificanceinimprovingtheefficiencyofroadtransportat
2、ionandtestingofvehiclecharging.Firstly,thepaperbasedonvideodetectiondiscusseshoapthroughtheseoperationssuchasimagepre-processing,vehiclesegmentationandcontourextractiontoderivegeometricalparametersofvehicleswhichareusedtoestablishthevectorbyacorrelationanalysis.Secondly,weus
3、ethesefeaturevectorstobu5678910试议基于BP神经X络的车型识别毕业设计论文_(2)导读:bytheclassificationfunctionissimpleandeasytoimplementhardofvehicleclassificationbasedonBPNeuralNetaintasksareasfolloentationmethodbasedonbackgroundsubtraction.Itcansolvetheproblemofvehicledetectioninplextrafficsituat
4、ionseffectively.(2)Featureextraction.Accordingtotheneedsofvehicleclassification,softheparameterstolaidthefoundationofvehicleclassification.Thispaperfinallyadoptsthevectorsoftheratiooftopandlength,topandheight,foreters.Theresultofapplicationandsimulationindicatesthatthereal-t
5、imequality,accuracyandotherperformancesimprovedandthevehicleclassificationsystemachievesprospectiveobjectives.Atthesametime,ourapproachhasfollople,theaccountissmall,andtheBPpleandeasytoimplementhardware,whichwillhelpclassific5678910试议基于BP神经X络的车型识别毕业设计论文_(3)导读:.............3第
6、2章车辆目标检测..............................................................................................................42.1基于视频图像的车型识别系统简介..........................................................................42.2视频图像序列采集.................ationandrecognition.Keywords:ITS;Ve
7、hicleRecognition;VehicleDetection;FeatureExtraction;BPNeuralNetwork扬州大学本科生毕业设计目录第1章绪论..............................................................................................................................11.1课题研究的背景和意义..................................................
8、............................................11.2国内外车型识别技术的研究现状.............
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