Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1815009(2022)

Expression Recognition Based on Attention-Split Convolutional Residual Network

Jiamin Chen1 and Yang Xu1,2、*
Author Affiliations
  • 1College of Big Data and Information Engineering , Guizhou University, Guiyang 550025, Guizhou , China
  • 2Guiyang Aluminum-Magnesium Design and Research Institute Co. Ltd., Guiyang 550009, Guizhou , China
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    References(27)

    [1] Yin P B, Pan W M, Zhang H J. Lightweight facial expression recognition method based on convolutional attention[J]. Laser & Optoelectronics Progress, 58, 1210023(2021).

    [2] Yao L S, Xu G M, Zhao F. Facial expression recognition based on local feature fusion of convolutional neural network[J]. Laser & Optoelectronics Progress, 57, 041513(2020).

    [3] Yang X, Shang Z H. Facial expression recognition based on improved AlexNet[J]. Laser & Optoelectronics Progress, 57, 243-250(2020).

    [5] Wu H H, Su H S, Liu G H et al. Facial expression recognition algorithm based on cosine distance loss function[J]. Laser & Optoelectronics Progress, 56, 241502(2019).

    [22] Liang H G, Lei Y X. Expression recognition with separable convolution channel enhancement features[J]. Computer Engineering and Applications, 58, 184-192(2022).

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    Jiamin Chen, Yang Xu. Expression Recognition Based on Attention-Split Convolutional Residual Network[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1815009

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    Paper Information

    Category: Machine Vision

    Received: Jun. 11, 2021

    Accepted: Aug. 10, 2021

    Published Online: Aug. 30, 2022

    The Author Email: Xu Yang (xuy@gzu.edu.cn)

    DOI:10.3788/LOP202259.1815009

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