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基于改进YOLO11n-seg模型的人参幼苗分拣算法

刘泽 刘亚磊 宋伟 邬圣贤 黄东岩

吉林农业大学学报2026,Vol.48Issue(4):639-651,13.
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吉林农业大学学报2026,Vol.48Issue(4):639-651,13.DOI:10.13327/j.jjlau.2026.0203

基于改进YOLO11n-seg模型的人参幼苗分拣算法

Ginseng Seedling Sorting Algorithm Based on an Improved YOLO11n-seg Model

刘泽 1刘亚磊 1宋伟 1邬圣贤 1黄东岩1

作者信息

  • 1. 吉林农业大学工程技术学院,长春 130118
  • 折叠

摘要

Abstract

To improve the automation and intelligence of ginseng seedling sorting prior to transplan-tation,this study proposed a DBE-YOLO11-seg ginseng seedling recognition model to address the challenges of small seedling targets,slender roots,severe occlusion and adhesion,and insufficient segmentation accuracy under complex illumination backgrounds.The proposed model used YOLO11n-seg as the baseline.A DCNv4-C3k2 module was constructed in the backbone network to enhance the geometric modeling capability for slender and curved targets.A P2 feature layer and an HFFE module were introduced into the neck to improve the preservation of shallow texture details and the effectiveness of multi-scale feature fusion.In the segmentation head,CARAFE upsampling and a boundary-assisted supervision strategy were adopted to construct a CARAFE-Edge-Head seg-mentation and detection head,thereby improving mask boundary recovery and separation of adherent targets.Training and testing were conducted on a self-constructed ginseng seedling dataset,followed by validation on a sorting system test bench.The results showed that the proposed model achieved an mAP@0.5 of 92.7%,a segmentation mAP@0.5 of 87.2%,a BIoU of 80.9%,and a sorting accuracy of 96.1%,demonstrating superior overall performance compared with those of Mask R-CNN,YOLACT++,YOLOv8n-seg,and YOLO11n-seg.Therefore,the proposed method can effectively im-prove the recognition and segmentation performance of ginseng seedlings in complex sorting environ-ments,and possesses promising potential for engineering applications.

关键词

智能分拣/人参幼苗/边界监督/动态可变形卷积/多尺度特征融合

Key words

intelligent sorting/ginseng seedling/boundary supervision/dynamic deformable con-volution/multi-scale feature fusion

分类

农业科技

引用本文复制引用

刘泽,刘亚磊,宋伟,邬圣贤,黄东岩..基于改进YOLO11n-seg模型的人参幼苗分拣算法[J].吉林农业大学学报,2026,48(4):639-651,13.

基金项目

吉林省科技发展计划项目(20260204066YY) (20260204066YY)

吉林农业大学学报

1000-5684

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