Ridge navigation line extraction for rapeseed transplanters based on R-YOLOv11-Prune

Smart Agricultural Technology 2026 Open access

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Authors: Wei Han, Yang Xiang, Mingliang Wu, Yong Zeng, Ruikun Zou, Xiaohu Jiang, Wei Quan
DOI: 10.1016/j.atech.2026.101797
Cited by: 2
References: 20

Abstract

• A lightweight ridge instance segmentation model (R-YOLOv11-Prune) was developed. • Large-kernel Ghost-DW and Dir-SE modules enhance ridge feature representation. • BN sparsity-guided pruning reduced parameters by 82% with 0.992 mAP maintained. • A dynamic centerline and piecewise fitting algorithm ensured smooth navigation lines. • The embedded system achieved 23.9 ms per frame with

Fields of Study & Subjects

Smart Agriculture and AI Soil Mechanics and Vehicle Dynamics Irrigation Practices and Water Management

Publication details

Journal / source
Smart Agricultural Technology
Publisher
Elsevier BV
Volume
13
Pages
101797–101797
Publication date
11 January 2026
Language
EN