Deep Learning Based Growth Analysis and Disease Detection in Strawberry Cultivation

Basit Öğe Kaydı
dc.contributor.authorAyberguler, Azad
dc.contributor.authorArslan, Enis
dc.contributor.authorKayaarma, Selma Yilmazyildiz
dc.date.accessioned2026-02-12T21:02:48Z
dc.date.available2026-02-12T21:02:48Z
dc.date.issued2023
dc.departmentBursa Teknik Üniversitesi
dc.description2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023 -- 2023-10-11 through 2023-10-13 -- Sivas -- 194153
dc.description.abstractStrawberry cultivation can be susceptible to unforeseen diseases. For the prevention of Powdery Mildew and Gray Mold diseases prompt pesticide applications should be carried out during the disease development or periodically, aligned with strawberries' growth stages. In this study, a deep learning-based growth stage analysis and disease detection solution was developed. Three versions of the YOLO architecture (YOLOv5, YOLOv3, YOLOv3-tiny) have been trained on a dataset that was enhanced for this specific use case. YOLOv3-tiny version was also deployed on a simple unmanned ground vehicle in a real-life strawberry cultivation greenhouse. This study differs from others in the literature by training and deploying a model that would enable the detection of both powdery mildew disease and the growth stages of strawberries in a single model. With the deployment of this model, the strawberry growers can implement the appropriate spraying strategies that would control and prevent the formation and spread of these diseases. © 2023 IEEE.
dc.identifier.doi10.1109/ASYU58738.2023.10296697
dc.identifier.isbn9798350306590
dc.identifier.scopus2-s2.0-85178307289
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ASYU58738.2023.10296697
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6536
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.snmzKA_Scopus_20260212
dc.subjectComputer Vision
dc.subjectGrowth and Disease Analysis
dc.subjectStrawberry
dc.subjectYOLO
dc.titleDeep Learning Based Growth Analysis and Disease Detection in Strawberry Cultivation
dc.typeConference Object

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu