Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2526
Title: AnEnsembleofTransferLearningbasedInceptionV3andVGG16Mo delsforPaddyLeafDiseaseClassi cation
Authors: Sowmiya, B
Saminathan, K
ChithraDevi, M
Keywords: PaddyLeafDis-eases,Classi cation,TransferLearning,Ensemble,Incep-tionetV3,VGG16,DeepLearning
Issue Date: 8-May-2024
Publisher: Bharathidasa University
Abstract: Paddyisacrucialfo o dcropprovidingessentialnutrientsandenergyandservingmorethanhalftheglobalp opulation.Diagnosingandpreventingplantdiseasesatanearlystageiscrucialforthehealthandpro ductivityofcrops.Automateddiseasediagnosiseliminatestheneedforexp ertsanddeliversaccurateoutcomes.ThisresearchwilldiagnosepaddyleafdiseaseswithDeepLearningtechnology.Thediseasessuchasbacterialblight,blast,tungro,brownsp ot,andhealthyleafclassesarediagnosedandclassi edinthisstudy.Thedatasetcontains160imagesfromeachclasswith800im-ages.Ourprop osedmo delisanensembleoftransfer-learnedInceptionV3andVGG16architectures,whichutilizesthestrengthofindividualmo d-elstoimproveoverallp erformance.Theuseoftransfer-learnedensembledeeplearningarchitecturesachievedimpressiveaccuracyratesof97.03%,94.97%,and98.87%fortraining,validationandtestingresp ectively.Theresultsindicatingthatmo delisnotover tandgeneralizeswelltounseendata.Themo del'sp erformanceisevaluatedwithconfusionmatrixwiththeparameterslikeprecision,recall,F1-score,andsupp ort.Wealsotestedthemo del'sp erformanceagainstotherprop oseddeeplearningtechniqueswithandwithouttransferlearningtechniques.Moreover,thisresearchad-vancesreliableautomateddiseasedetectionsystems,fosteringsustainableagricultureandenhancingglobalfo o dsecurity
URI: http://localhost:8080/xmlui/handle/123456789/2526
ISSN: 2286-9131
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