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    Cherry Tree Detection with Deep Learning
    (Institute of Electrical and Electronics Engineers Inc., 2022) Ozer, Tolga; Akdogan, Cemalettin; Cengiz, Enes; Kelek, Muhammed Mustafa; Yildirim, Kasim; Oguz, Yuksel; Akkoc, Hasan
    In 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.