Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field Environments Article Swipe
Chunming Wen
,
Cheng Yang
,
Shangping Li
,
Leilei Liu
,
Quanquan Liang
,
Kaihua Li
,
Youzong Huang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15084286
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15084286
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.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app15084286
- https://www.mdpi.com/2076-3417/15/8/4286/pdf?version=1744533581
- OA Status
- gold
- References
- 15
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409433753
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https://openalex.org/W4409433753Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app15084286Digital Object Identifier
- Title
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Slim-YOLO: An Improved Sugarcane Tail Tip Recognition Algorithm Based on YOLO11n for Complex Field EnvironmentsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-13Full publication date if available
- Authors
-
Chunming Wen, Cheng Yang, Shangping Li, Leilei Liu, Quanquan Liang, Kaihua Li, Youzong HuangList of authors in order
- Landing page
-
https://doi.org/10.3390/app15084286Publisher landing page
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https://www.mdpi.com/2076-3417/15/8/4286/pdf?version=1744533581Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2076-3417/15/8/4286/pdf?version=1744533581Direct OA link when available
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Computer science, Artificial intelligence, Computer vision, Algorithm, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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15Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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