資源描述：
《Automatic Localization of Casting Defects withConvolutional Neural Networks 鑄件缺陷的自動定位 卷積神經網絡》由會員上傳分享，免費在線閱讀，更多相關內容在學術論文-天天文庫。
1、AutomaticLocalizationofCastingDefectswithConvolutionalNeuralNetworksMaxFergusonRonayAkYung-TsunTinaLeeKinchoH.LawEngineeringInformaticsGroupSystemsIntegrationDivisionSystemsIntegrationDivisionEngineeringInformaticsGroupCivilandEnvironmentalNationalInsti
2、tuteofStandardsNationalInstituteofStandardsCivilandEnvironmentalEngineeringandTechnology(NIST)andTechnology(NIST)EngineeringStanfordUniversityGaithersburg,UnitedStatesGaithersburg,UnitedStatesStanfordUniversityStanford,UnitedStatesronay.ak@nist.govyung-
3、tsun.lee@nist.govStanford,UnitedStatesmaxferg@stanford.edulaw@stanford.eduAbstract—AutomaticlocalizationofdefectsinmetalcastingsisThereareanumberofnondestructiveexamination(NDE)achallengingtask,owingtotherareoccurrenceandvariationintechniquesavailablefo
4、rproducingtwo-dimensionalandthree-appearanceofdefects.Convolutionalneuralnetworks(CNN)havedimensionalimagesofanobject.Real-timeX-rayimagingrecentlyshownoutstandingperformanceinbothimagetechnologyiswidelyusedindefectdetectionsystemsinclassificationandloc
5、alizationtasks.Weexaminehowseveralindustry,suchason-linewelddefectinspection[3].UltrasonicdifferentCNNarchitecturescanbeusedtolocalizecastingdefectsinspectionandmagneticparticleinspectioncanalsobeusedtoinX-rayimages.Wetakeadvantageoftransferlearningtoal
6、lowmeasurethesizeandpositionofcastingdefectsincaststate-of-the-artCNNlocalizationmodelstobetrainedonacomponents[4,5].Analternativemethodisthree-dimensionalrelativelysmalldataset.Inanalternativeapproach,wetrainaX-raycomputedtomography,thatcanbeusedtovisu
7、alizethedefectclassificationmodelonaseriesofdefectimagesandtheninternalstructureofmaterials.RecentdevelopmentsinhighuseaslidingclassifiermethodtodevelopasimplelocalizationresolutionX-raycomputedtomographyhavemadeitpossibletomodel.Wecomparethelocalizatio
8、naccuracyandcomputationalgainathree-dimensionalcharacterizationofporosity[6,7].performanceofeachtechnique.WeshowpromisingresultsfordefectlocalizationontheGRIMAdatabaseofX-rayimagesThedefectdetectionprocesscanbeframedaseitheran(GD
