Segmentation-Based Detection for Luffa Seedling Grading Using the Seg-FL Model

Segmentation-Based Detection for Luffa Seedling Grading Using the Seg-FL Model

This study addresses the issue of inaccurate and error-prone grading judgments in luffa plug seedlings. A new Seg-FL seedling segmentation model is proposed as an extension of the YOLOv5s-Seg model. The small leaves of early-stage luffa seedlings are liable to be mistaken for impurities in the plug...

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Bibliographic Details
Main Authors: Sheng Jiang, Fangnan Xie, Jiangbo Ao, Yechen Wei, Jingye Lu, Shilei Lyu, Zhen Li
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Agronomy
Subjects:
YOLOv5s-seg
seedling segmentation
channel attention module
CIoU loss function
grading efficiency
Online Access:https://www.mdpi.com/2073-4395/14/11/2557
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