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1、biosystemsengineering151(2016)72e80Availableonlineatwww.sciencedirect.comScienceDirectjournalhomepage:www.elsevier.com/locate/issn/15375110ResearchPaperPlantspeciesclassi?cationusingdeepconvolutionalneuralnetworka,*baMadsDyrmann,HenrikKarstoft,HenrikSkovMidtibyaTheMaerskMc-KinneyMolle
2、rInstitute,UniversityofSouthernDenmark,DenmarkbDepartmentofEngineering,AarhusUniversity,DenmarkarticleinfoInformationonwhichweedspeciesarepresentwithinagricultural?eldsisimportantforArticlehistory:sitespeci?cweedmanagement.Thispaperpresentsamethodthatiscapableofrecog-Received16March20
3、16nisingplantspeciesincolourimagesbyusingaconvolutionalneuralnetwork.TheReceivedinrevisedformnetworkisbuiltfromscratchtrainedandtestedonatotalof10,413imagescontaining2222August2016weedandcropspeciesatearlygrowthstages.TheseimagesoriginatefromsixdifferentAccepted26August2016datasets,wh
4、ichhavevariationswithrespecttolighting,resolution,andsoiltype.Thisincludesimagestakenundercontrolledconditionswithregardtocamerastabilisationandillumination,andimagesshotwithhand-heldmobilephonesin?eldswithchangingKeywords:lightingconditionsanddifferentsoiltypes.Forthese22species,then
5、etworkisabletoPlantclassi?cationachieveaclassi?cationaccuracyof86.2%.Deeplearning?2016IAgrE.PublishedbyElsevierLtd.Allrightsreserved.ConvolutionalNeuralNetworksWeedcontrolWeedcontrolmethods,whichrelyonmechanicalmeans,1.Introductionneedtoknowthepreciselocationofcropplants,whilemethodst
6、hatoptimisetheherbicideapplicationrequiresin-Inmodernfarming,thereisaneedforeffectiveweedcontrolformationonthespeciesoftheweedplants.Byusingdetailedasyieldlossescausedbynotcontrollingtheweedsaresig-informationaboutpresentweedplantspecies,theirgrowthni?cant(23%e71%dependingonthecrops,w
7、eedsandloca-stagesandplantdensitiesina?eld,theherbicideconsump-tion(Hodgson,1968;Oerke,2006;Slaughter,Giles,Fennimore,tioncanbereducedby40%onaverage(J?rgensenetal.,2007).&Smith,2008)).ThepreferredmethodusedforcontrollingTheDanishsystem,CropProtectionOnline,isatoolthathelpsweedsistoapp
8、lyher