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基于YOLO的电梯轿厢中狗识别算法.docx

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基于YOLO的电梯轿厢中狗识别算法为题目，写不少于1200的论文 I.Introduction Inrecentyears,objectdetectionhasbecomeoneofthecoretasksincomputervisionresearch.OneofthemostpopularobjectdetectionalgorithmsisYOLO(YouOnlyLookOnce),whichisanend-to-endlearningmodelthatcanquicklyandaccuratelydetectobjectsinimagesandvideos.Withthedevelopmentofdeeplearningtechnology,YOLOhasbeenwidelyusedinvariousfields,suchasautonomousdriving,surveillance,androbotics. Inthispaper,weproposeaYOLO-basedalgorithmforidentifyingdogsinelevatorcabins.Elevatorsareessentialfacilitiesinbuildings,anddogsarecommonlyfoundinresidentialbuildings,offices,andotherpublicspaces.However,dogsinelevatorscanposearisktootherpassengers,particularlythosewhohaveallergiesorfearofdogs.Therefore,itiscrucialtoidentifydogsintheelevatorcabinquicklyandaccuratelytoensurethesafetyofpassengers. II.RelatedWork Objectdetectionhasbeenwidelystudiedinrecentyears,andseveralalgorithmshavebeenproposed.Traditionalmethods,suchasslidingwindows,requiremultiplepassesofimagescanning,whichisinefficientandtime-consuming.Recently,deeplearning-baseddetectionalgorithmshaveachievedgreatsuccessinobjectdetection.YOLOisoneofthemostrepresentativealgorithms,whichhasbeenwidelyusedinmanyfields. However,applyingYOLOtodogdetectioninelevatorcabinsisstillanewresearchdirection.Somestudieshavebeenconductedtodetectdogsinimagesandvideos,butthesemethodsmaynotbesuitableforelevatorcabins'uniqueenvironment.Therefore,weproposeaYOLO-basedalgorithmspecificallydesignedfordogdetectioninelevatorcabins. III.Methodology Ourdogdetectionalgorithmconsistsofthreemainstages:datacollection,networktraining,anddogdetection.First,wecollectedadatasetofimagescontainingdogsinelevatorcabins.Thisdatasetincludesvariousdogbreeds,differentelevatorcabins,anddifferentlightingconditions. Then,wetrainedaYOLOv3objectdetectionmodelonthecollecteddatasettorecognizedogsinelevatorcabins.TheYOLOv3modelisaneuralnetworkthatusesasingleconvolutionalneuralnetwork(CNN)topredictboundingboxesandclassprobabilitiesfortheobjectsinanimage.Compa