YOLOv11-SMS: An Improved Algorithm for Impurity Detection in Seed Cotton.

Wenyan Yuan, Laigang Zhang, Donghe Wang, Zhijun Guo

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Wenyan YuanSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.

Laigang ZhangSchool of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China.ORCID 0000-0002-5565-0364

Donghe WangChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Zhijun GuoInstitute of Information Science and Technology, Hunan Normal University, Changsha 410081, China.

Funding

Department of Science and Technology of Shandong Province ZR2022ME303Liaocheng University 318012013

6 · The paper itself

Abstract

To enhance the precision of cottonseed impurity detection and address issues such as high miss-detection rates and suboptimal performance, this paper introduces an improved YOLOv11 algorithm, termed YOLOv11-SMS. Initially, the algorithm integrates a local self-attention mechanism (LRSA) to design the C2PSA-SL module, which augments the model's ability to learn local information while maintaining global feature awareness. Furthermore, the feature extraction stage and the network head incorporate a multi-branch reparameterized convolution (MBRConv) module, enhancing feature extraction capabilities while preserving the model's lightweight properties. Lastly, a spatial adaptive modulation (SAFM) module is introduced to optimize the detection of small targets. Experimental results demonstrate that YOLOv11-SMS outperforms the baseline model, with mAP@

Indexed as

LRSAMBRConvSAFMseed cotton impurity detectionYOLOv11

Identifiers

PMID42122556

DOI10.3390/s26092835

PMCPMC13165815

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LicenceCC BY

Read underepoch 390

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.