Deep Learning-Based Detection of Honey Storage Areas in <i>Apis mellifera</i> Colonies for Predicting Physical Parameters of Honey via Linear Regression

Traditional methods for assessing honey storage in beehives predominantly rely on manual visual inspection, which often leads to inconsistencies and inefficiencies. This study presents an automated deep learning approach utilizing the YOLOv11 model to detect, classify, and quantify honey cells withi...

وصف كامل

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Watit Khokthong, Panpakorn Kritangkoon, Chainarong Sinpoo, Phuwasit Takioawong, Patcharin Phokasem, Terd Disayathanoowat
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	MDPI AG 2025-05-01
سلاسل:	Insects
الموضوعات:	honeybee hive classification deep learning image processing object detection YOLO honey quantification
الوصول للمادة أونلاين:	https://www.mdpi.com/2075-4450/16/6/575
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!