Enhanced YOLO11n-Seg with Attention Mechanism and Geometric Metric Optimization for Instance Segmentation of Ripe Blueberries in Complex Greenhouse Environments

Enhanced YOLO11n-Seg with Attention Mechanism and Geometric Metric Optimization for Instance Segmentation of Ripe Blueberries in Complex Greenhouse Environments

This study proposes an improved YOLO11n-seg instance segmentation model to address the limitations of existing models in accurately identifying mature blueberries in complex greenhouse environments. Current methods often lack sufficient accuracy when dealing with complex scenarios, such as fruit occ...

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Bibliographic Details
Main Authors: Rongxiang Luo, Rongrui Zhao, Bangjin Yi
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Agriculture
Subjects:
YOLO11n-seg
instance segmentation
spatial–channel adaptive attention (SCA)
dual attention balance module (DAB)
normalized wasserstein distance (NWD)
complex greenhouse environments
Online Access:https://www.mdpi.com/2077-0472/15/15/1697
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https://www.mdpi.com/2077-0472/15/15/1697

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