• Electronics Optics & Control
  • Vol. 28, Issue 11, 31 (2021)
LI Chen1、2, CHEN Hao3, and LI Jianxun1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2021.11.007 Cite this Article
    LI Chen, CHEN Hao, LI Jianxun. An Effectiveness Evaluation Indicator System Based on Multi-Scale Parallel Convolution Neural Network[J]. Electronics Optics & Control, 2021, 28(11): 31 Copy Citation Text show less
    References

    [1] DENG X, ZENG D, SHEN H.Causation analysis model:based on AHP and hybrid apriori-genetic algorithm[J].Journal of Intelligent & Fuzzy Systems, 2018, 35(1): 767-778.

    [2] LI X L, LU J Y, GAO Z B, et al.Effectiveness evaluation of kill chain based on PCA, AHP and entropy weight method[C]//Proceedings of the 3rd International Confe-rence on Modelling, Simulation and Applied Mathematics(MSAM), 2018: 192-196.

    [5] FAN Q, GAO D.A fast BP networks with dynamic sample selection for handwritten recognition[J].Pattern Analysis and Applications, 2018, 21(1):67-80.

    [12] SZEGEDY C, LIU W, JIA Y, et al.Going deeper with convolutions[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Bos-ton, IEEE, 2015:1-9.

    LI Chen, CHEN Hao, LI Jianxun. An Effectiveness Evaluation Indicator System Based on Multi-Scale Parallel Convolution Neural Network[J]. Electronics Optics & Control, 2021, 28(11): 31
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