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International Journal of Pavement Engineering Volume 23, 2022 - Issue 6
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Articles

Automated pavement distress detection using region based convolutional neural networks

Eldor Ibragimova Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of KoreaView further author information
,
Hyun-Jong Leea Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of KoreaView further author information
,
Jong-Jae Leea Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of KoreaORCID Iconhttps://orcid.org/0000-0001-6157-0419View further author information
ORCID Icon &
Namgyu Kimb Department of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology (KICT), Goyang-Si, Republic of KoreaCorrespondence[email protected] [email protected]
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Pages 1981-1992 | Received 03 Jul 2019, Accepted 02 Oct 2020, Published online: 24 Oct 2020

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Haimei Liang, Hongren Gong, Lin Cong, Miaomiao Zhang, Zefeng Tao, Shifu Liu & Jiachen Shi. (2023) Automated detection of airfield pavement damages: an efficient light-weight algorithm. International Journal of Pavement Engineering 24:1.
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Shuo Ding, Hong Lang, Jiang Chen, Ye Yuan & Jian Lu. (2023) Automated crack segmentation on 3D asphalt surfaces with richer attention and hybrid pyramid structures. International Journal of Pavement Engineering 24:1.
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Xuetang Xiong & Yiqiu Tan. (2023) Pixel-Level patch detection from full-scale asphalt pavement images based on deep learning. International Journal of Pavement Engineering 24:1.
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Maryam Samie, Amir Golroo, Donya Tavakoli & Mohammadsadegh Fahmani. (2023) Potential applications of connected vehicles in pavement condition evaluation: a brief review. Road Materials and Pavement Design 0:0, pages 1-25.
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G. Bosurgi, M. Modica, O. Pellegrino & G. Sollazzo. (2023) An automatic pothole detection algorithm using pavement 3D data. International Journal of Pavement Engineering 24:2.
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Cheng Chen, Hyungjoon Seo & Yang Zhao. (2022) A novel pavement transverse cracks detection model using WT-CNN and STFT-CNN for smartphone data analysis. International Journal of Pavement Engineering 23:12, pages 4372-4384.
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Gang Li, Dongchao Lan, Xuan Zheng, Xue Li & Jian Zhou. (2022) Automatic pavement crack detection based on single stage salient-instance segmentation and concatenated feature pyramid network. International Journal of Pavement Engineering 23:12, pages 4206-4222.
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Junzhi Zhai, Zhaoyun Sun, Ju Huyan, Handuo Yang & Wei Li. (2022) Automatic pavement crack detection using multimodal features fusion deep neural network. International Journal of Pavement Engineering 0:0, pages 1-14.
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Parisa Setayesh Valipour, Amir Golroo, Afarin Kheirati, Mohammadsadegh Fahmani & Mohammad Javad Amani. Automatic pavement distress severity detection using deep learning. Road Materials and Pavement Design 0:0, pages 1-17.
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Articles from other publishers (19)

Yu-Ting Huang, Mohammad R. JahanshahiFangjia Shen & Tarutal Ghosh Mondal. (2023) Deep Learning–Based Autonomous Road Condition Assessment Leveraging Inexpensive RGB and Depth Sensors and Heterogeneous Data Fusion: Pothole Detection and Quantification. Journal of Transportation Engineering, Part B: Pavements 149:2.
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Sike WangXueqin ChenQiao Dong. (2023) Detection of Asphalt Pavement Cracks Based on Vision Transformer Improved YOLO V5. Journal of Transportation Engineering, Part B: Pavements 149:2.
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Zhaoyun Sun, Junzhi Zhai, Lili Pei, Wei Li & Kaiyue Zhao. (2023) Automatic Pavement Crack Detection Transformer Based on Convolutional and Sequential Feature Fusion. Sensors 23:7, pages 3772.
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Esma Dilek & Murat Dener. (2023) Computer Vision Applications in Intelligent Transportation Systems: A Survey. Sensors 23:6, pages 2938.
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Elham Eslami & Hae-Bum Yun. (2023) Comparison of deep convolutional neural network classifiers and the effect of scale encoding for automated pavement assessment. Journal of Traffic and Transportation Engineering (English Edition).
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Pengcheng Wang, Chao Wang, Hongwu Liu, Ming Liang, Wenhui Zheng, Hao Wang, Shichao Zhu, Guoqiang Zhong & Shang Liu. (2023) Research on Automatic Pavement Crack Recognition Based on the Mask R-CNN Model. Coatings 13:2, pages 430.
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Chuan Xu, Qi Zhang, Liye Mei, Sen Shen, Zhaoyi Ye, Di Li, Wei Yang & Xiangyang Zhou. (2023) Dense Multiscale Feature Learning Transformer Embedding Cross-Shaped Attention for Road Damage Detection. Electronics 12:4, pages 898.
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Junzhi Zhai, Zhaoyun Sun, Ju Huyan, Wei Li & Handuo Yang. (2023) Feature representation improved Faster R-CNN model for high-efficiency pavement crack detection. Canadian Journal of Civil Engineering 50:2, pages 114-125.
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Ayman H. El Hakea & Mohamed W. Fakhr. (2023) Recent computer vision applications for pavement distress and condition assessment. Automation in Construction 146, pages 104664.
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Wei-Wei Jin, Guo-Hong Chen, Zhuo Chen, Yun-Lei Sun, Jie Ni, Hao Huang, Wai-Hung Ip & Kai-Leung Yung. (2022) Road Pavement Damage Detection Based on Local Minimum of Grayscale and Feature Fusion. Applied Sciences 12:24, pages 13006.
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Hao Liu, Yishun Li, Chenglong Liu, Guohong Shen & Hui Xiang. (2022) Pavement Distress Initiation Prediction by Time-Lag Analysis and Logistic Regression. Applied Sciences 12:22, pages 11855.
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Lan Qiao, Nai-Fu Deng, Qing-Wen Li, Qing-Long Zhang & Jia-Wang Hao. (2022) Multi-CrackNet: A Fast Segmentation and Quantification Combined Method for Rock Discontinuity Traces by Capturing an Image. Geofluids 2022, pages 1-22.
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Langyue Zhao, Yiquan Wu, Xudong Luo & Yubin Yuan. (2022) Automatic Defect Detection of Pavement Diseases. Remote Sensing 14:19, pages 4836.
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Wenhao Tang, Sheng Huang, Qiming Zhao, Ren Li & Luwen Huangfu. (2022) An Iteratively Optimized Patch Label Inference Network for Automatic Pavement Distress Detection. IEEE Transactions on Intelligent Transportation Systems 23:7, pages 8652-8661.
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Juncheng Guo, Yuyan Wu, Lizhi Chen, Shangbin Long, Daqi Chen, Haibing Ouyang, Chunliang Zhang, Yadong Tang & Wenlong Wang. (2022) A perspective on the diagnosis of cracked tooth: imaging modalities evolve to AI-based analysis. BioMedical Engineering OnLine 21:1.
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Luqman Ali, Fady Alnajjar, Wasif Khan, Mohamed Adel Serhani & Hamad Al Jassmi. (2022) Bibliometric Analysis and Review of Deep Learning-Based Crack Detection Literature Published between 2010 and 2022. Buildings 12:4, pages 432.
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Hongwen Dong, Kechen Song, Qi Wang, Yunhui Yan & Peng Jiang. (2022) Deep Metric Learning-Based for Multi-Target Few-Shot Pavement Distress Classification. IEEE Transactions on Industrial Informatics 18:3, pages 1801-1810.
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Furkan BALCI & Safiye YILMAZ. (2022) Faster R-CNN Structure for Computer Vision-based Road Pavement Distress Detection. Journal of Polytechnic.
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Xu Yang, Jinchao Guan, Ling Ding, Zhanping You, Vincent C.S. Lee, Mohd Rosli Mohd Hasan & Xiaoyun Cheng. (2021) Research and applications of artificial neural network in pavement engineering: A state-of-the-art review. Journal of Traffic and Transportation Engineering (English Edition) 8:6, pages 1000-1021.
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