Spectroscopy and Spectral Analysis, Volume. 43, Issue 9, 2928(2023)

Identification of Maize Varieties by Hyperspectral Combined With Extreme Learning Machine

ZHANG Fu1, WANG Xin-yue2, CUI Xia-hua2, YU Huang2, CAO Wei-hua2, ZHANG Ya-kun2, XIONG Ying3, and FU San-ling4
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  • 1[in Chinese]
  • 2[in Chinese]
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  • 4[in Chinese]
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    References(7)

    [6] [6] Huang M, He C J, Zhu Q B, et al. Applied Sciences, 2016, 6(6): 183.

    [7] [7] Xia C, Yang S, Huang M, et al. Infrared Physics & Technology, 2019, 103: 103077.

    [8] [8] Chivasa W, Mutanga O, Biradar C. Journal of Applied Remote Sensing, 2019, 13(1): 017504.

    [9] [9] Zhou Q, Huang W Q, Tian X, et al. Journal of the Science of Food and Agriculture, 2021, 101(11): 4532.

    [10] [10] Sun H, Zhang L, Li H, et al. Journal of Food Process Engineering, 2021, 44(8): 13769.

    [11] [11] Singh T, Garg N M, Iyengar S R S. Journal of Food Process Engineering, 2021, 44(10): 13821.

    [18] [18] Wu J, Mohamed D, Dowhanik S, et al. Plant Cell, 2020, 32(6): 1886.

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    ZHANG Fu, WANG Xin-yue, CUI Xia-hua, YU Huang, CAO Wei-hua, ZHANG Ya-kun, XIONG Ying, FU San-ling. Identification of Maize Varieties by Hyperspectral Combined With Extreme Learning Machine[J]. Spectroscopy and Spectral Analysis, 2023, 43(9): 2928

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    Paper Information

    Received: Apr. 29, 2022

    Accepted: --

    Published Online: Jan. 12, 2024

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2023)09-2928-07

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