• Optoelectronics Letters
  • Vol. 19, Issue 1, 60 (2023)
Jingyi LIU1、2、3, Lina YU1、2、3, Linjun SUN1、2、3, Yuerong TONG1、2、3, Min WU1、2、3, and Weijun and LI1、2、3、4、*
Author Affiliations
  • 1Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
  • 22. Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology, Beijing 100083, China
  • 3School of Integrated Circuits, University of Chinese Academy of Sciences, Beijing 100049, China
  • 4Shenzhen DAPU Microelectronics Co., Ltd., Shenzhen 518116, China
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    DOI: 10.1007/s11801-023-2065-6 Cite this Article
    LIU Jingyi, YU Lina, SUN Linjun, TONG Yuerong, WU Min, and LI Weijun. Fitting objects with implicit polynomials by deep neural network[J]. Optoelectronics Letters, 2023, 19(1): 60 Copy Citation Text show less
    References

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    [17] WANG G J, LI W J, ZHANG L P, et al. Encoder-X: solving unknown coefficients automatically in polynomial fitting by using an autoencoder[J]. IEEE transactions on networks and learning systems, 2022, 33(8): 3264-3276.

    [18] ZHENG B, TAKAMATSU J, IKEUCHI K. An adaptive and stable method for fitting implicit polynomial curves and surfaces[J]. IEEE transactions on pattern analysis & machine intelligence, 2010, 32(3):561-568.

    LIU Jingyi, YU Lina, SUN Linjun, TONG Yuerong, WU Min, and LI Weijun. Fitting objects with implicit polynomials by deep neural network[J]. Optoelectronics Letters, 2023, 19(1): 60
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