Journal of Applied Optics, Volume. 44, Issue 4, 792(2023)
Bridge disease detection and recognition based on improved YOLOX algorithm
[2] [2] JIA Xiaoyu. Research on bridge crack identification and measurement method based on convolutional neural network[D]. Liuzhou: Guangxi University of Science and Technology, 2019.
[5] [5] ZHANG Ning. Research on highway pavement disease detection algorithm based on Faster R-CNN[D]. Nanchang: East China Jiaotong University, 2019.
[6] [6] ZHANG C, CHANG C, JAMSHIDI M. Concrete bridge surface damage detection using a single stage detector[J]. Computer Aided Civil and Infrastructure Engineering, 2020, 35(4):389-409.
[9] [9] CHEN Xianchang. Research on deep learning algorithm and application based on convolutional neural network[D]. Hangzhou: Zhejiang Gongshang University, 2014.
[11] [11] WANG C Y , LIAO H , WU Y H , et al. CSPNet: A new backbone that can enhance learning capability of CNN[C]// 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). New York: IEEE, 2020.
[13] [13] TAN M, PANG R, LE Q V. Efficientdet: Scalable and efficient object detection[C]//Procee dings of the IEEE/CVF conference on computer vision and pattern recognition.New York: IEEE, 2020: 10781-10790.
[14] [14] HU J, SHEN L, SUN G. Squeeze-and-excitation networks[C]//Proceedings of the IEEE co nference on computer vision and pattern recognition. New York: IEEE, 2018: 7132-7141.
[15] [15] WOO S, PARK J, LEE J Y, et al. Cbam: Convolutional block attention module[C]//Procee dings of the European conference on computer vision (ECCV). New York: IEEE,2018: 3-19.
[16] [16] HOU Q, ZHOU D, FENG J. Coordinate attention for efficient mobile network design[C]// Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2021: 13713-13722.
[17] [17] MUNDT M, MAJUMDER S, MURALI S, et al. Meta-learning convolutional neural archit ectures for multi-target concrete defect classification with the concrete defect bridge image dataset[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Re cognition. New York: IEEE, 2019: 11196-11205.
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Yanna LIAO, Liang YAO. Bridge disease detection and recognition based on improved YOLOX algorithm[J]. Journal of Applied Optics, 2023, 44(4): 792
Category: Research Articles
Received: Jul. 7, 2022
Accepted: --
Published Online: Aug. 10, 2023
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