Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 1, 118(2023)

Lightweight smoke and fire detection algorithm based on efficient global context network

Lun-sheng WEI1, Wang-ming XU1,2、*, Jing-yuan ZHANG1, and Bin CHEN1
Author Affiliations
  • 1School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China
  • 2Engineering Research Center for Metallurgical Automation and Detecting Technology of Ministry of Education,Wuhan University of Science and Technology,Wuhan 430081,China
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    References(28)

    [8] REN S Q, HE K M, GIRSHICK R et al. Faster R-CNN: Towards real-time object detection with region proposal networks[C], 91-99(2015).

    [12] BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: optimal speed and accuracy of object detection[J]. arXiv, 2004.10934(2020).

    [19] GE Z, LIU S T, WANG F et al. YOLOX: exceeding YOLO series in 2021[J]. arXiv, 2107.08430(2021).

    [23] NAIR V, HINTON G E. Rectified linear units improve restricted Boltzmann machines[C], 807-814(2010).

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    Lun-sheng WEI, Wang-ming XU, Jing-yuan ZHANG, Bin CHEN. Lightweight smoke and fire detection algorithm based on efficient global context network[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(1): 118

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    Paper Information

    Category: Research Articles

    Received: Jun. 1, 2022

    Accepted: --

    Published Online: Feb. 20, 2023

    The Author Email: Wang-ming XU (xuwangming@wust.edu.cn)

    DOI:10.37188/CJLCD.2022-0184

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