Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1815001(2022)

Detection Method of Downpipe Diseases Based on Visual Attention Mechanism

Jiasong Zhu1,2、**, Tianzhu Ma1,3、***, Haokun Yang1,3, Xu Fang2,4, and Qing Li1、*
Author Affiliations
  • 1Institute of Urban Smart Transportation & Safety Maintenance, Shenzhen 518000, Guangdong , China
  • 2Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518000, Guangdong , China
  • 3College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518000, Guangdong , China
  • 4College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518000, Guangdong , China
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    References(20)

    [1] Wang M X, Fan J J, Zhou L et al. Automatic detection and classification of sewer defects via deep learning revoke[J]. Water & Wastewater Engineering, 56, 106-111(2020).

    [6] Shan Q W, Zheng X B, He X H et al. Fast object detection and recognition algorithm based on improved multi-scale feature maps[J]. Laser & Optoelectronics Progress, 56, 021002(2019).

    [12] Liu X, Chen S Y, Chen X L et al. Deep multi-scale feature fusion target detection algorithm based on deep learning[J]. Laser & Optoelectronics Progress, 58, 1210029(2021).

    [20] Guo L, Zhang T S, Sun W Z et al. Image semantic description algorithm with integrated spatial attention mechanism[J]. Laser & Optoelectronics Progress, 58, 1210030(2021).

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    Jiasong Zhu, Tianzhu Ma, Haokun Yang, Xu Fang, Qing Li. Detection Method of Downpipe Diseases Based on Visual Attention Mechanism[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1815001

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    Paper Information

    Category: Machine Vision

    Received: Jun. 11, 2021

    Accepted: Jul. 20, 2021

    Published Online: Aug. 30, 2022

    The Author Email: Zhu Jiasong (zjsong@szu.edu.cn), Ma Tianzhu (1910473004@email.szu.edu.cn), Li Qing (qingli@szu.edu.cn)

    DOI:10.3788/LOP202259.1815001

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