Comparative analysis of convolutional neural network architectures for classification of plant leaf diseases

Basit Öğe Kaydı
dc.contributor.authorAl Heeti, Fatimah
dc.contributor.authorIlyas, Muhammad
dc.date.accessioned2025-02-06T17:58:22Z
dc.date.available2025-02-06T17:58:22Z
dc.date.issued2022
dc.departmentAltınbaş Üniversitesien_US
dc.description2nd International Conference on Computing and Machine Intelligence (ICMI) -- JUL 15-16, 2022 -- Istanbul, TURKEYen_US
dc.description.abstractPlants play an essential role in the life of any living organism, human or animal, so protecting this organism from disease is an urgent necessity for the survival of living organisms. The development of science has reduced the time required to discover a disease, allowing us to detect and treat diseases early using artificial intelligence. In this scientific paper, we compared the performance of (Vgg-16, MobileNet, and ConvNext) through time and accuracy among these models. We trained these models by using transfer learning models of convolutional neural networks (CNN) to classify plant diseases (potatoes, tomatoes, and peppers). We used a dataset containing 20,639 images divided into 15 classes of different diseases, we also used the same number of parameter and the same number of layers in vgg16 and mobilenet but in convnext 24 layers.The dataset from the Kaggle site and the work environment on google colab using Python language. The results are shown vgg-16 is a high accuracy of 0.97 during the training process from convnext and mobilenet,but MobilNet is faster in the time 62s.en_US
dc.description.sponsorshipIEEE Turkey Sect,Istanbul Atlas Univ, Dept Comp Engnen_US
dc.identifier.doi10.1109/ICMI55296.2022.9873752
dc.identifier.endpage158en_US
dc.identifier.isbn978-1-6654-7484-9
dc.identifier.isbn978-1-6654-7483-2
dc.identifier.scopus2-s2.0-85139052406
dc.identifier.startpage154en_US
dc.identifier.urihttps://doi.org/10.1109/ICMI55296.2022.9873752
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5199
dc.identifier.wosWOS:001340389000031
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2022 2nd International Conference on Computing and Machine Intelligence, Icmi 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_WOS_20250206
dc.subjectVgg-16en_US
dc.subjectMobileNeten_US
dc.subjectConvNexten_US
dc.subjectColaben_US
dc.subjecttransferm learningen_US
dc.titleComparative analysis of convolutional neural network architectures for classification of plant leaf diseasesen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu