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

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Název: Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field Environments.
Autoři: Wen, Chunming, Cheng, Yang, Li, Shangping, Liu, Leilei, Liang, Qingquan, Li, Kaihua, Huang, Youzong
Zdroj: Applied Sciences (2076-3417); Apr2025, Vol. 15 Issue 8, p4286, 19p
Témata: FEATURE extraction, REAL-time control, SUGARCANE, SPINE, ALGORITHMS
Abstrakt: 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 backbone, an ELANSlimNeck neck structure, and the Unified-IoU (UIoU) loss function. Experimental results on the sugarcane tailing dataset show that Slim-YOLO achieves an mAP50 of 92.2% and mAP50:95 of 48.2%, outperforming YOLO11n by 8.2% and 6.1%, respectively, while reducing parameters by 48.4%. The enhanced accuracy and lightweight design make it suitable for practical deployment, offering theoretical and technical support for the automation control of sugarcane harvesters. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt: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 backbone, an ELANSlimNeck neck structure, and the Unified-IoU (UIoU) loss function. Experimental results on the sugarcane tailing dataset show that Slim-YOLO achieves an mAP50 of 92.2% and mAP50:95 of 48.2%, outperforming YOLO11n by 8.2% and 6.1%, respectively, while reducing parameters by 48.4%. The enhanced accuracy and lightweight design make it suitable for practical deployment, offering theoretical and technical support for the automation control of sugarcane harvesters. [ABSTRACT FROM AUTHOR]
ISSN:20763417
DOI:10.3390/app15084286