Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 8, 1139(2023)

Mask wearing detection based on improved YOLOv7

Hui-chen FU1,2, Jun-wei GAO1,2、*, and Lu-yang CHE1,2
Author Affiliations
  • 1School of Automation, Qingdao University, Qingdao 266071, China
  • 2Shandong Key Laboratory of Industrial Control Technology, Qingdao 266071, China
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    References(19)

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    [2] CAO S Z, WEN D S, CHEN X et al. Protective behavior of Chinese population wearing masks during the COVID-19 epidemic[J]. Research of Environmental Sciences, 33, 1649-1658(2020).

    [6] ZENG G H, YANG G Z, GUO S N et al. Design and application of real-time mask detection system[J]. Video Engineering, 46, 65-67(2022).

    [10] MA S S, WANG J, CAO S Z et al. Overview on two-dimensional human pose estimation methods based on deep learning[J]. Computer Systems & Applications, 31, 36-43(2022).

    [13] DING Y, WANG X, YAN X L. Edge adaptive four-point piecewise parabolic scaler implementation[J]. Journal of Zhejiang University (Engineering Science), 44, 1637-1642(2010).

    [17] DOSOVITSKIY A, BEYER L, KOLESNIKOV A et al. An image is worth 16×16 words: transformers for image recognition at scale[C], 1909-1931(2021).

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    Hui-chen FU, Jun-wei GAO, Lu-yang CHE. Mask wearing detection based on improved YOLOv7[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(8): 1139

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    Paper Information

    Category: Research Articles

    Received: Nov. 8, 2022

    Accepted: --

    Published Online: Oct. 9, 2023

    The Author Email: Jun-wei GAO (qdgao163@163.com)

    DOI:10.37188/CJLCD.2022-0371

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