Laser & Optoelectronics Progress, Volume. 58, Issue 6, 610007(2021)

Identification of Rice Diseases Based on Batch Normalization and AlexNet Network

Yang Hongyun1, Wan Ying2, Wang Yinglong2、*, and Luo Jianjun2
Author Affiliations
  • 1School of Software, Jiangxi Agricultural University, Nanchang, Jiangxi 330045, China
  • 2School of Computer Information and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi 330045, China
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    References(28)

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    [13] Wu L L, Zheng Z X, Qi L et al. Detection method of rice leaf blast based on image processing[J]. Journal of Agricultural Mechanization Research, 36, 32-35(2014).

    [15] Liu C. Study on identification algorithm of rice diseases based on machine learning[D]. Hefei: Anhui University(2018).

    [17] Liu T T, Wang T, Hu L. Rhizocotonia solani recognition algorithm based on convolutional neural network[J]. Chinese Journal of Rice Science, 33, 90-94(2019).

    [20] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [23] Ioffe S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift[EB/OL]. (2015-02-11)[2020-07-02]. https://arxiv.org/abs/1502.03167.

    [26] Nah S, Kim T H, Lee K M. Deepmulti-scale convolutional neural network for dynamic scene deblurring[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 257-265(2017).

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    Yang Hongyun, Wan Ying, Wang Yinglong, Luo Jianjun. Identification of Rice Diseases Based on Batch Normalization and AlexNet Network[J]. Laser & Optoelectronics Progress, 2021, 58(6): 610007

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    Paper Information

    Category: Image Processing

    Received: Jul. 20, 2020

    Accepted: --

    Published Online: Mar. 11, 2021

    The Author Email: Yinglong Wang (83577939@qq.com)

    DOI:10.3788/LOP202158.0610007

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