• Spectroscopy and Spectral Analysis
  • Vol. 42, Issue 10, 3226 (2022)
Rong-hua GAO1、*, Lu FENG1、1; 2; *;, Yue ZHANG3、3;, Ji-dong YUAN3、3;, Hua-rui WU1、1; 2;, and Jing-qiu GU1、1; 2;
Author Affiliations
  • 11. Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
  • 33. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
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    DOI: 10.3964/j.issn.1000-0593(2022)10-3226-09 Cite this Article
    Rong-hua GAO, Lu FENG, Yue ZHANG, Ji-dong YUAN, Hua-rui WU, Jing-qiu GU. Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image[J]. Spectroscopy and Spectral Analysis, 2022, 42(10): 3226 Copy Citation Text show less
    References

    [7] Xiaohong Wu, Jun Sun, Xin Zhou et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 212, 215(2019).

    [9] Guijun Yang, Ning Zhang, Y C Pan et al. Remote Sensing, 12, 3188(2020).

    [10] C Xie, Y He, C Yang. Computers and Electronics in Agriculture, 135, 154(2017).

    [11] B Lucas, C Pelletier, A Shifaz et al. Data Mining and Knowledge Discovery, 33, 607(2019).

    Rong-hua GAO, Lu FENG, Yue ZHANG, Ji-dong YUAN, Hua-rui WU, Jing-qiu GU. Early Detection of Tomato Gray Mold Disease With Multi-Dimensional Random Forest Based on Hyperspectral Image[J]. Spectroscopy and Spectral Analysis, 2022, 42(10): 3226
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