A Blueberry Maturity Detection Method Integrating Attention-Driven Multi-Scale Feature Interaction and Dynamic Upsampling

A Blueberry Maturity Detection Method Integrating Attention-Driven Multi-Scale Feature Interaction and Dynamic Upsampling

In the context of blueberry orchard management and automated harvesting, this study introduces an improved YOLOv8 model, ADE-YOLO, designed for precise blueberry ripeness detection, enhancing automated picking efficiency. Built on the YOLOv8n architecture, ADE-YOLO features a dimensionality-reducing...

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Bibliographic Details
Main Authors: Haohai You, Zhiyi Li, Zhanchen Wei, Lijuan Zhang, Xinhua Bi, Chunguang Bi, Xuefang Li, Yunpeng Duan
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Horticulturae
Subjects:
YOLOv8
deep learning
target recognition
EIOU
blueberry
Online Access:https://www.mdpi.com/2311-7524/11/6/600
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