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Corn field weed detection method based on improved YOLOv5s
Updated：2026-06-22
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    • Corn field weed detection method based on improved YOLOv5s

    • “The research team proposed a detection method based on improved YOLOv5s to address issues such as insufficient real-time detection of weeds in corn fields, complex models, and difficult deployment. By embedding a lightweight GhostNetV3 module, introducing CA attention mechanism, and EIoU loss function, the method achieves dual improvements in model lightweighting and detection accuracy, providing an efficient solution for weed recognition in smart agriculture.”
    • WANG Ning , SHANG Zhong , CHEN Kang , LYU Haotun , JIA Lin , YAO Yu
    • Journal of China Agricultural University Vol. 31, Issue 2, Pages: 192-204(2026)

    • DOI： 10.11841/j.issn.1007-4333.2026.02.17     

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