Automatic Maize Leaf Disease Recognition Using Deep Learning

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dc.contributor.authorÇakmak, Muhammet
dc.date.accessioned2025-03-23T19:17:20Z
dc.date.available2025-03-23T19:17:20Z
dc.date.issued2024
dc.departmentSinop Üniversitesi
dc.description.abstractMaize leaf diseases exhibit visible symptoms and are currently diagnosed by expert pathologists through personal observation, but the slow manual detection methods and pathologist's skill influence make it challenging to identify diseases in maize leaves. Therefore, computer-aided diagnostic systems offer a promising solution for disease detection issues. While traditional machine learning methods require perfect manual feature extraction for image classification, deep learning networks extract image features autonomously and function without pre-processing. This study proposes using the EfficientNet deep learning model for the classification of maize leaf diseases and compares it with another established deep learning model. The maize leaf disease dataset was used to train all models, with 4188 images for the original dataset and 6176 images for the augmented dataset. The proposed models were compared with ResNet50, VGG19, DenseNet121 and Inception V3 models according to their accuracy, sensitivity, F1-Score and precision values. The EfficientNet B6 model achieved 98.10% accuracy on the original dataset, while the EfficientNet B3 model achieved the highest accuracy of 99.66% on the augmented dataset. © 2024, Sakarya University. All rights reserved.
dc.identifier.doi10.35377/saucis...1418505
dc.identifier.endpage76
dc.identifier.issn2636-8129
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85207941429
dc.identifier.scopusqualityN/A
dc.identifier.startpage61
dc.identifier.trdizinid1233747
dc.identifier.urihttps://doi.org/10.35377/saucis...1418505
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1233747
dc.identifier.urihttps://hdl.handle.net/11486/4311
dc.identifier.volume7
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.institutionauthorÇakmak, Muhammet
dc.language.isoen
dc.publisherSakarya University
dc.relation.ispartofSakarya University Journal of Computer and Information Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_Scopus_20250323
dc.subjectDeep learning
dc.subjectPlant disease classification
dc.subjectTransfer learning
dc.titleAutomatic Maize Leaf Disease Recognition Using Deep Learning
dc.typeArticle

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