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Slicing Angle Recognition of Fritillariae Thunbergii Bulbus Based on Improved YOLOv7-tiny Algorithm
更新时间：2024-04-30
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    • Slicing Angle Recognition of Fritillariae Thunbergii Bulbus Based on Improved YOLOv7-tiny Algorithm

    • “针对浙贝母切片角度的自动识别问题，研究团队提出了一种基于改进YOLOv7-tiny算法的解决方案。该研究通过数据增广构建了丰富的浙贝母图像数据集，并对原算法进行了多方面的优化。实验结果显示，改进后的算法在参数量、计算量、识别精度和速度等方面均有了显著提升。具体来说，参数量减少至原算法的55.4%，计算量减少至59.4%，IoU为0.5时的平均精度均值提升了12.2%，识别角度的平均绝对误差降低了4.58°，单张图片平均识别时间更是达到了8.7ms，远快于人类平均反应时间。这一研究不仅为浙贝母切片的自动化识别提供了新方法，也为其他中药的自动化炮制提供了有益的参考。”
    • Chinese Journal of Experimental Traditional Medical Formulae   Vol. 30, Issue 11, Pages: 183-191(2024)

    • DOI：10.13422/j.cnki.syfjx.20240365    

      CLC： R22;TP75;R28;R943.1

    • Published：05 June 2024，

      Published Online：07 December 2023，

      Received：31 August 2023，

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  • YUE Xingchen,DU Weifeng,LU Shengli,et al.Slicing Angle Recognition of Fritillariae Thunbergii Bulbus Based on Improved YOLOv7-tiny Algorithm[J].Chinese Journal of Experimental Traditional Medical Formulae,2024,30(11):183-191. DOI： 10.13422/j.cnki.syfjx.20240365.

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