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

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...

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Bibliographic Details
Main Authors: Watit Khokthong, Panpakorn Kritangkoon, Chainarong Sinpoo, Phuwasit Takioawong, Patcharin Phokasem, Terd Disayathanoowat
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Insects
Subjects:
honeybee hive classification
deep learning
image processing
object detection
YOLO
honey quantification
Online Access:https://www.mdpi.com/2075-4450/16/6/575
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