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《Automatic Fruit Recognition Based on DCNN for Commercial Source Trace System》由會(huì)員上傳分享，免費(fèi)在線閱讀，更多相關(guān)內(nèi)容在學(xué)術(shù)論文-天天文庫(kù)。
1、碩士留學(xué)生學(xué)位論文AutomaticFruitRecognitionBasedonDCNNforCommercialSourceTraceSystem作者姓名HussainIsrar學(xué)科專業(yè)信息與通信工程指導(dǎo)教師賀前華所在學(xué)院電子信息與通信工程學(xué)院論文提交日期2018年05月日AutomaticFruitRecognitionBasedonDCNNforCommercialSourceTraceSystemADissertationSubmittedfortheDegreeofMasterCandidat
2、e:HussainIsrarSupervisor:Prof.HeQianHua賀前華SouthChinaUniversityofTechnologyGuangzhou,ChinaABSTRACTAutomaticfruitrecognition-basedonmachinevisionisconsideredaschallengingtaskduetosimilaritiesbetweenvarioustypesoffruitsandexternalenvironmentalchangese-glight
3、ing.Fruitandvegetableclassificationisoneofthemajorapplicationsthatcanbeutilizedinsupermarketandfruitshopstoautomaticallydetectandrecognizethekindoffruitsandvegetablespurchasedbycustomersandtodetermineitsprices.Althoughautomaticfruitrecognitionisgettingmor
4、eandmoreimportant,thistechnologyisstillfarfrombeingmature.Themainworkandinnovationsofthisthesisareasfollows:(1)AfruitrecognitionalgorithmbasedondeepconvolutionneuralNetwork(DCNN)isproposed.Mostoftheprevioustechniqueshavesomelimitationsbecausetheywereexami
5、nedandevaluatedunderlimiteddataset,furthermoretheyhavenotconsideredexternalenvironmentalchanges.Weevaluatedourmodelinmuchmorecomplicateddatasetwhichmostlymeetallreal-worldchallengestomakeourmodelrobust.(2)Weestablishedfruitimagesdatabasespanning15differen
6、tcategorieswhichcompriseof44406imagescollectedinourlabenvironmentduringaperiodof6monthsunderdifferentreal-worldconditions&keepinginviewthelimitationsofexistingdataset.(3)WealsoproposeanalgorithmforIntra-classrecognitionoffruitsusingDCNN(deepconvolutionaln
7、euralnetwork).Theresultsofcarryingouttheseexperimentsdemonstratethattheproposedapproachcouldbeautomaticallyrecognizethefruitwithaccuracyof99%.TheInputimagesweredirectlyinputtoDCNNfortrainingandrecognitionwithoutfeaturesextraction&theDCNNlearnoptimalfeatur
8、esfromimagesadaptively.Thefinaldecisionwasmadebasedonafusionofallregionsclassificationusingprobabilitymechanism.Keyword:FruitRecognition;Deeplearning;DeepConvolutionalNeuralNetworkITableofContentABSTRACT............
