Journal of Optoelectronics · Laser, Volume. 33, Issue 11, 1165(2022)

Automatic detection of pavement defects based on deep learning

WANG Xin and LI Qi*
Author Affiliations
  • [in Chinese]
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    References(17)

    [2] [2] CHEN F C,JAHANSHAHI M R,WU R T,et al.A texture-based video processing methodology using Bayesian data fusion for autonomous crack detection on metallic surfaces[J].Computer-Aided Civil and Infrastructure Engineering,2017,32(4):271-287.

    [3] [3] CUBERO-FERNANDEZ A, RODRIGUEZ-LOZANO F, Vil- latoro R,et al.Efficient pavement crack detection and classification[J].EURASIP Journal on Image and Video Processing,2017,2017(1):1-11.

    [4] [4] REN S,HE K,GIRSHICK R,et al.Faster R-CNN:towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2017,39(6):1137-1149.

    [5] [5] LIU W,Anguelov D,Erhan D,et al.SSD:single shot multibox detector[C]//European Conference on Computer Vision,October 11-14,2016,Amsterdam,The Netherlands.Singapore:Springer,2016:21-37.

    [6] [6] Redmon J, Divvala S, Girshick R, et al. You only look once:unified,real-time object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition,June 27-30,2016,Las Vegas,NV,USA.New York:IEEE,2016:779-788.

    [7] [7] GIRSHICK R.Fast R-CNN[C]//IEEE International Conference on Computer Vision,December 7-13,2015,NW Washington,DC,United States.New York:IEEE,2015:1440-1448.

    [8] [8] SUH G,CHA Y J.Deep faster R-CNN-based automated detection and localization of multiple types of damage[C]//Sensors and Smart Structures Technologies for Civil,Mechanical,and Aerospace Systems 2018,March 4-8,2018,Denver,Colorado,United States.Washington:SPIE,2018,10598:105980T.

    [9] [9] CHA Y J,CHOI W,SUH G,et al.Autonomous structural visual inspection using region-based deep learning for detecting multiple damage types[J].Computer-Aided Civil and Infrastructure Engineering,2018,33(9):731-747.

    [10] [10] FANG F,LI L,GU Y,et al.A novel hybrid approach for crack detection[J].Pattern Recognition,2020,107:107474.

    [11] [11] MAEDA H,SEKIMOTO Y,SETO T,et al.Road damage detection and classification using deep neural networks with smartphone images[J].Computer-Aided Civil and Infrastructure Engineering,2018,33(12):1127-1141.

    [12] [12] MAEDA H,KASHIYAMA T,SEKIMOTO Y,et al.Generative adversarial network for road damage detection[J].Computer-Aided Civil and Infrastructure Engineering,2021,36(1):47-60.

    [13] [13] REDMON J,FARHADI A.YOLO9000:better,faster,stronger[C]//IEEE Conference on Computer Vision and Pattern Recognition,July 21-26,2017,Hawaii,USA.New York:IEEE,2017:7263-7271.

    [14] [14] REDMON J,FARHADI A.Yolov3:an incremental improvement[EB/OL].(2018-04-08)[2022-02-12].http://arxiv.org/abs/1804.02767.

    [15] [15] BOCHKOVSKIY A,WANG C Y,LIAO H Y M.Yolov4:optimal speed and accuracy of object detection[EB/OL].(2020-04-23)[2022-02-12].http://arxiv.org/abs/2004.10934.

    [16] [16] GE Z,LIU S,WANG F,et al.Yolox:exceeding yolo series in 2021[EB/OL].(2021-07-18)[2022-02-12].http://arxiv.org/abs/2107.08430.

    [17] [17] MANDAL V,MUSSAH A R,ADU-GYAMFI Y.Deep learning frameworks for pavement distress classification: A comparative analysis[C]//2020 IEEE International Conference on Big Data (Big Data),December 10-13,2020,Atlanta,GA,USA.New York:IEEE,2020:5577-5583.

    [18] [18] ZHOU X,WANG D,KRAHENBUHL P.Objects as points[EB/OL].(2019-04-16)[2022-02-12].http://arxiv.org/abs/1904.07850.

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    WANG Xin, LI Qi. Automatic detection of pavement defects based on deep learning[J]. Journal of Optoelectronics · Laser, 2022, 33(11): 1165

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    Paper Information

    Received: Feb. 12, 2022

    Accepted: --

    Published Online: Oct. 9, 2024

    The Author Email: LI Qi (richey@imust.edu.cn)

    DOI:10.16136/j.joel.2022.11.0074

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