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Discovery of agricultural diseases by deep learning and object detection

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dc.contributor.authorÇELEBİ, MEHMET FATİH
dc.contributor.authorERSOY, SEZGİN
dc.contributor.authorsKarakaya M., Çelebi M. F., Gok A. E., Ersoy S.
dc.date.accessioned2023-03-28T07:15:05Z
dc.date.available2023-03-28T07:15:05Z
dc.date.issued2022-01-01
dc.description.abstractIn this study deep learning and object detection models for image-based plant disease recognition have been carried. Trained models were tested on pictures and in real-time with a video camera for five different diseases in tomato leaves. Object detection algorithm was implemented from the personal computer, and deep learning models were applied via Google Colab. Real-time object detection was achieved in the developed model with YOLOv5 algorithm with the highest accuracy of 93.38% in validation accuracy and 94.48% in training accuracy with the highest value of 92.96% in precision. Furthermore, it has been observed that YOLOv5 algorithm gives faster and more accurate results than the previous versions of YOLO.
dc.identifier.citationKarakaya M., Çelebi M. F., Gok A. E., Ersoy S., "DISCOVERY OF AGRICULTURAL DISEASES BY DEEP LEARNING AND OBJECT DETECTION", ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, cilt.21, sa.1, ss.163-173, 2022
dc.identifier.endpage173
dc.identifier.issn1582-9596
dc.identifier.issue1
dc.identifier.startpage163
dc.identifier.urihttps://eds.s.ebscohost.com/eds/pdfviewer/pdfviewer?vid=0&sid=1cc345dd-7c61-4a92-a031-63227f4f87c8%40redis
dc.identifier.urihttps://hdl.handle.net/11424/287968
dc.identifier.volume21
dc.language.isoeng
dc.relation.ispartofENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectTarımsal Bilimler
dc.subjectÇevre Mühendisliği
dc.subjectMühendislik ve Teknoloji
dc.subjectAgricultural Sciences
dc.subjectEnvironmental Engineering
dc.subjectEngineering and Technology
dc.subjectÇEVRE BİLİMLERİ
dc.subjectÇevre / Ekoloji
dc.subjectTarım ve Çevre Bilimleri (AGE)
dc.subjectENVIRONMENTAL SCIENCES
dc.subjectENVIRONMENT/ECOLOGY
dc.subjectAgriculture & Environment Sciences (AGE)
dc.subjectAquatic Science
dc.subjectNature and Landscape Conservation
dc.subjectEnvironmental Science (miscellaneous)
dc.subjectPhysical Sciences
dc.subjectLife Sciences
dc.subjectagricultural disease
dc.subjectdeep learning
dc.subjectdisease detection
dc.subjectobject detection
dc.titleDiscovery of agricultural diseases by deep learning and object detection
dc.typearticle
dspace.entity.typePublication
local.avesis.idf56168e1-ee26-43d4-b2ba-33f61c9b420e
local.indexed.atWOS
local.indexed.atSCOPUS
relation.isAuthorOfPublicationc6058d21-5ade-4488-b230-8e13eae5066a
relation.isAuthorOfPublicationeea24e32-3704-4272-87de-e30b5c4e4c1e
relation.isAuthorOfPublication.latestForDiscoveryc6058d21-5ade-4488-b230-8e13eae5066a

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