Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field Environments

Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field Environments

Accurate identification of the sugarcane tail tip is crucial for the real-time automation control of the harvester’s cutting device, improving harvesting efficiency, and reducing impurity rates. This paper proposes Slim-YOLO, an improved YOLO11n-based algorithm incorporating a lightweight RepViT bac...

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Bibliographic Details
Main Authors: Chunming Wen, Yang Cheng, Shangping Li, Leilei Liu, Qingquan Liang, Kaihua Li, Youzong Huang
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
complex environment
sugarcane tail tip
cutting area identification
multi-scale feature extraction
efficient feature fusion
Online Access:https://www.mdpi.com/2076-3417/15/8/4286
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