Performance comparison of convolutional neural network models for plant leaf disease classification

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dc.contributor.authorAl Heeti, Fatimah
dc.contributor.authorIlyas, Muhammad
dc.date.accessioned2022-12-22T10:23:57Z
dc.date.available2022-12-22T10:23:57Z
dc.date.issued2022en_US
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Bilişim Teknolojileri Ana Bilim Dalıen_US
dc.description.abstractAs food is an essential element in life, modern possibilities must be harnessed to pay attention to it. In this paper, we will discuss the discovery of early plant diseases classification using artificial intelligence technology, we made in this study analysis of convolutional neural networks architecture (vgg-16, mobile net, efficient net) and made a comparison between these model in accuracy and loos data in each model, we used data set from the Kaggle site that contain 20640 picture from different disease of plant (potato, tomato and pepper) this pictures divided on 15 class but unbalanced. at the first we solved the problem of train the models with multi class, we made balanced data and training the work in environment of Google Colab, we used it in train three models vgg-16, mobile net, efficient net, which showed this study that the accuracy of work in efficient net is 98% more than other models and loss data in this model is less than other models.en_US
dc.identifier.citationAl Heeti, F., Ilyas, M. (2022). Performance comparison of convolutional neural network models for plant leaf disease classification. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 386-391). IEEE.en_US
dc.identifier.endpage391en_US
dc.identifier.isbn9781665470131
dc.identifier.scopus2-s2.0-85142851212
dc.identifier.scopusqualityN/A
dc.identifier.startpage386en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3136
dc.indekslendigikaynakScopus
dc.institutionauthorAl Heeti, Fatimah
dc.institutionauthorIlyas, Muhammad
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
dc.relation.isversionof10.1109/ISMSIT56059.2022.9932655en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectEfficient Neten_US
dc.subjectGoogle Colaben_US
dc.subjectMobile Neten_US
dc.subjectTransform Learningen_US
dc.subjectVgg-16en_US
dc.titlePerformance comparison of convolutional neural network models for plant leaf disease classification
dc.typeConference Object

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