Laser Technology, Volume. 47, Issue 6, 831(2023)

3-D surface reconstruction based on structured light and deep neural network

DAI Jinke1, ZHENG Suzhen1、*, and SU Juan2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    References(21)

    [1] [1] MIN L, LI D, DONG Sh. 3D surface roughness measurement based on SFS method[C]//2017 8th International Conference on Intelligent Human-Machine Systems and Cybernetics(IHMSC). Hangzhou, Ch-ina: IEEE, 2017: 484-488.

    [2] [2] GUO X F, ZHANG Q C. Three-dimensional shape reconstruction based on BP neural network[J]. Laser Journal, 2019, 40(1): 40-41(in Chinese).

    [3] [3] GERON A. Hands-on machine learning with scikit-learn, keras, and tensorflow: Concepts, tools, and techniques to build intelligent systems[M]. 2th ed. Sebastopol, USA: O’Reilly Media, 2019: 220-226.

    [4] [4] THEOBALD O. Machine learning for absolute beginners: A plain english introduction[M]. Washington DC, USA: Amazon Publishing, 2019: 66-68.

    [5] [5] LIU Y Sh, WANG R M, ZHAO J J, et al. A novel robust variable selection algorithm for multilayer perceptron[C]//2022 13th Asian Control Conference(ASCC). Jeju, Korea: IEEE, 2022: 470-475.

    [6] [6] NIELSEN M. Neural networks and deep learning[M]. Berlin,Germany: Springer Publishing, 2019: 113-116.

    [7] [7] ZHOU Zh H. Machine learning[M]. Beijing: Tsinghua University Press, 2017: 35-48(in Chinese).

    [8] [8] KO B S, KIM H G, OH K J, et al. Controlled dropout: A different approach to using dropout on deep neural network[C]//2017 IEEE International Conference on Big Data and Smart Computing (BigComp). New York, USA: IEEE, 2017: 358-362.

    [9] [9] XIE Sh J, LI L. Improvement and application of deep belief network based on sparrow search algorithm[C]//2021 IEEE International Conference on Advances in Electrical Engineering and Computer A-pplications (AEECA). New York, USA: IEEE, 2021: 705-708.

    [10] [10] LI M, ZHANG C, TONG X L. Composite material impact location detection technology based on BP algorithm and FBG sensing[J]. Laser Technology, 2022,46(3): 320-325(in Chinese).

    [12] [12] YAN D X, AN Y, LI G H, et al. High-resolution reconstruction of FMT based on elastic net optimized by relaxed ADMM[J]. IEEE Transactions on Biomedical Engineering(Early Access), 2022,10(11): 1-10.

    [13] [13] GONG F X, GONG T R, YU Y, et al. An electricity load forecasting algorithm based on kernel lasso regression[C]//2021 IEEE 4th International Electrical and Energy Conference (CIEEC). New York, USA: IEEE, 2021: 1-4.

    [14] [14] LI D, GE Q F, ZHANG P Ch, et al. Ridge regression with high order truncated gradient descent method[C]//2020 12th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC). New York, USA: IEEE, 2020: 252-255.

    [15] [15] LIU L, LUO Y H, SHEN X, et al. β-Dropout: A unified dropout[J]. IEEE Access, 2019,7(3): 36140-36153.

    [16] [16] SMITH R, KANDIMALLA V A K , REDDY G D. Predicting diabetes using outlier detection and multilayer perceptron with optimal stochastic gradient descent[C]//2020 IEEE India Council International Subsections Conference (INDISCON). New York, USA: IEEE, 2022: 51-56.

    [17] [17] PATTERSON J, GIBSON A. Deep learning: A practitioners a-pproach[M]. Sebastopol, USA: O’Reilly Published,2019: 402-406.

    [18] [18] KHANIKI M A L, HADI M B, MANTHOURI M. Feedback error learning controller based on RMSprop and salp swarm algorithm for automatic voltage regulator system[C]//2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). New York, USA: IEEE, 2020: 425-430.

    [19] [19] GOODFELLOW I, BENGIO Y. Deep learning[M]. Beijing: Posts Telecom Press, 2017: 53-79(in Chinese).

    [20] [20] MA Y Y, WANG L D. Study on distortion correction and optimization of optical measurement system based on neural network[J]. Laser Journal, 2017,37(11): 42-45(in Chinese).

    [21] [21] GERON A. Hands-on machine learning with scikit-learn and tensorflow[M]. 2th ed. Sebastopol, USA: O’Reilly Media, 2020: 576-579.

    Tools

    Get Citation

    Copy Citation Text

    DAI Jinke, ZHENG Suzhen, SU Juan. 3-D surface reconstruction based on structured light and deep neural network[J]. Laser Technology, 2023, 47(6): 831

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Sep. 26, 2022

    Accepted: --

    Published Online: Dec. 5, 2023

    The Author Email: ZHENG Suzhen (suzhen317@swpu.edu.cn)

    DOI:10.7510/jgjs.issn.1001-3806.2023.06.015

    Topics