Optical Technique, Volume. 50, Issue 6, 706(2024)

Method of indoor visible light positioning based on hybrid neural network

LI Nan* and BAI Yufeng
Author Affiliations
  • School of Modern Logistics, Shanxi Vocational University of Engineering Science and Technology, Jingzhong 030619, China
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    References(11)

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    [14] [14] Hsu L, Tsai D, Chen H M, et al. Using received-signal-strength (RSS) pre-processing and convolutional neural network (CNN) to enhance position accuracy in visible light positioning (VLP)[J].2022 Optical Fiber Communications Conference and Exhibition (OFC),2022,3(2):1—3.

    [15] [15] He J, Hsu C W, Zhou Q, et al. Demonstration of high precision 3D indoor positioning system based on two-layer ANN machine learning technique[C]∥Optical Fiber Communication Conference. San Diego,USA:IEEE,2019:23—27.

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    [18] [18] Li S, Qin L, Zhao D, et al. Indoor positioning system for single LED light based on deep residual shrinkage network[J]. Optics Communications,2024,55(9):130366—130373.

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    LI Nan, BAI Yufeng. Method of indoor visible light positioning based on hybrid neural network[J]. Optical Technique, 2024, 50(6): 706

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    Paper Information

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    Received: May. 6, 2024

    Accepted: Jan. 21, 2025

    Published Online: Jan. 21, 2025

    The Author Email: Nan LI (linan182600@sohu.com)

    DOI:

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