Spectroscopy and Spectral Analysis, Volume. 41, Issue 3, 898(2021)

Early Detection and Identification of Rice Blast Based on Hyperspectral Image

KANG Li1,2, YUAN Jian-qing3, GAO Rui1, KONG Qing-ming1, JIA Yin-jiang1, and SU Zhong-bin1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(7)

    [1] [1] De Morsier F, Borgeaud M, Gass V, et al. IEEE Transactions on Geoscience & Remote Sensing, 2016, 54(6): 3410.

    [2] [2] Nijat Kasim, Shi Qingdong, Wang Jingzhe, et al. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(22): 208.

    [3] [3] Wang J, Wu W, Wang T, et al. Spectroscopy Letters, 2018, 51(9): 485.

    [4] [4] Wang Y, Jiang F, Gupta B B, et al. IEEE Access, 2018, 6: 5290.

    [6] [6] Lu J, Zhou M, Gao Y, et al. Precision Agriculture, 2018, 19(3): 379.

    [7] [7] Ashourloo D, Aghighi H, Matkan A A, et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(9): 4344.

    CLP Journals

    [1] LI Bin, SU Cheng-tao, YIN Hai, LIU Yan-de. Hyperspectral Imaging Technology Combined With Machine Learning for Detection of Moldy Rice[J]. Spectroscopy and Spectral Analysis, 2023, 43(8): 2391

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    KANG Li, YUAN Jian-qing, GAO Rui, KONG Qing-ming, JIA Yin-jiang, SU Zhong-bin. Early Detection and Identification of Rice Blast Based on Hyperspectral Image[J]. Spectroscopy and Spectral Analysis, 2021, 41(3): 898

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    Paper Information

    Received: Apr. 8, 2020

    Accepted: --

    Published Online: Apr. 7, 2021

    The Author Email:

    DOI:10.3964/j.issn.1000-0593(2021)03-0898-05

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