Cherry Tree Detection with Deep Learning

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dc.contributor.authorOzer, Tolga
dc.contributor.authorAkdogan, Cemalettin
dc.contributor.authorCengiz, Enes
dc.contributor.authorKelek, Muhammed Mustafa
dc.contributor.authorYildirim, Kasim
dc.contributor.authorOguz, Yuksel
dc.contributor.authorAkkoc, Hasan
dc.date.accessioned2025-03-23T19:16:39Z
dc.date.available2025-03-23T19:16:39Z
dc.date.issued2022
dc.departmentSinop Üniversitesi
dc.description2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 -- 7 September 2022 through 9 September 2022 -- Antalya -- 183936
dc.description.abstractIn recent years, many studies have been conducted on artificial intelligence. Artificial-intelligence-based applications appear in many fields, such as the defense industry, agriculture, transportation, and health. Food production and supply are critical with the increase in the world population and global warming. For this reason, it is seen that various artificial-intelligence-based applications in agriculture are increasing today. In this study, artificial-intelligence-based Cherry tree detection was carried out using the deep learning method. A DJI Mavic air drone collected images of cherry trees in the Afyonkarahisar. A cherry tree dataset was created using these images. The training was carried out with YOLOv5m, YOLOv5s, and YOLOv5x models. As a result of the training, F1 scores of 94.20%, 98.0%, and 95.9% were obtained. The experimental results obtained as a result of the training of the models were shared comparatively. © 2022 IEEE.
dc.identifier.doi10.1109/ASYU56188.2022.9925332
dc.identifier.isbn978-166548894-5
dc.identifier.scopus2-s2.0-85142726613
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ASYU56188.2022.9925332
dc.identifier.urihttps://hdl.handle.net/11486/4169
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings - 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250323
dc.subjectAgriculture
dc.subjectArtificial Intelligent
dc.subjectCNN
dc.subjectDeep Learning
dc.subjectObject Detection
dc.subjectYOLO
dc.titleCherry Tree Detection with Deep Learning
dc.typeConference Object

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