Ünal, İ., & Eceoğlu, O. 2025 A lightweight instance segmentation model for simultaneous detection of citrus fruit ripeness and red scale (Aonidiella aurantii) pest damage. Applied Sciences 15: 9742
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Notes: This study aims to detect different ripeness stages and Red Scale damage in citrus fruits by a deep learning-based object segmentation method. In the study, a lighter and faster structure was created by developing the YOLO12n-Seg model to successfully identify small objects, especially under complex garden conditions. It is expected that this developed model will contribute to more efficient use of time, cost, and labor for producers by being integrated into early-warning systems in citrus orchards. https://doi.org/10.3390/app15179742
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