Journal of Applied Optics, Volume. 41, Issue 2, 327(2020)

Research on detection agorithm of solar cell component defects based on deep neural network

Huaiguang LIU1...2, Anyi LIU1,*, Shiyang ZHOU1,2, Hengyu LIU1 and Jintang YANG1 |Show fewer author(s)
Author Affiliations
  • 1Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Wuhan 430081, China
  • 2Institute of Robotics and Intelligent Systems, Wuhan University of Science and Technology, Wuhan 430081, China
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    References(13)

    [2] 钱晓亮, Xiaoliang QIAN, 张鹤庆, Heqing ZHANG, 陈永信, Yongxin CHEN. Research development and prospect of solar cells surface defects detection based on machine vision. Journal of Beijing University of Technology, 43, 76-85(2017).

    [6] Lei ZHANG, Peng LIANG, Huishi ZHU. Detection of finger interruptions in silicon solar cells using photoluminescence imaging. Chinese Physics B, 27, 556-561(2018).

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    [10] 伍李春, Lichun WU, 刘明周, Mingzhou LIU, 蒋倩男, Qiannan JIANG. Solar cell surface quality detection system based on artificial neural network. Journal of Hefei University of Technology: Natural Science, 40, 1176-1180(2017).

    [12] 杨帆, Fan YANG, 李建平, Jianping LI, 李鑫, Xin LI. Salient object detection algorithm based on multi-task deep convolutional neural network. Journal of Computer Applications, 91-96(2017).

    [13] [13] YAEE L , BOTTOU L,BENJIO Y. Gradientbased learning applied to document recognition[J]. USA:IEEE, 1998, 86(11):22782324.

    [14] N SRIVASTAVA, G HINTON, A KRIZHEVSKY. Dropout: a simple way to prevent neural networks from overfitting. Journal of Machine Learning Research, 15, 1929-1958(2014).

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    Huaiguang LIU, Anyi LIU, Shiyang ZHOU, Hengyu LIU, Jintang YANG. Research on detection agorithm of solar cell component defects based on deep neural network[J]. Journal of Applied Optics, 2020, 41(2): 327

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    Paper Information

    Category: OE INFORMATION ACQUISITION AND PROCESSING

    Received: Sep. 23, 2019

    Accepted: --

    Published Online: Apr. 23, 2020

    The Author Email: LIU Anyi (1609399877@qq.com)

    DOI:10.5768/JAO202041.0202006

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