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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V
Yue Fei, Kelvin C. P. Wang, Allen Zhang, et al.
IEEE Transactions on Intelligent Transportation Systems (2019) Vol. 21, Iss. 1, pp. 273-284
Closed Access | Times Cited: 263

Showing 1-25 of 263 citing articles:

A review of computer vision–based structural health monitoring at local and global levels
Chuan‐Zhi Dong, F. Necati Çatbaş
Structural Health Monitoring (2020) Vol. 20, Iss. 2, pp. 692-743
Closed Access | Times Cited: 533
Automated pavement crack detection and segmentation based on two‐step convolutional neural network
Jingwei Liu, Xu Yang, Stephen Lau, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 35, Iss. 11, pp. 1291-1305
Closed Access | Times Cited: 290
Machine Learning for Crack Detection: Review and Model Performance Comparison
Yung‐An Hsieh, Yichang Tsai
Journal of Computing in Civil Engineering (2020) Vol. 34, Iss. 5
Closed Access | Times Cited: 288
BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives
Mengqi Huang, Jelena Ninić, Qianbing Zhang
Tunnelling and Underground Space Technology (2020) Vol. 108, pp. 103677-103677
Open Access | Times Cited: 267
Structural crack detection using deep convolutional neural networks
Ali Raza, Joon Huang Chuah, Mohamad Sofian Abu Talip, et al.
Automation in Construction (2021) Vol. 133, pp. 103989-103989
Closed Access | Times Cited: 235
A critical review and comparative study on image segmentation-based techniques for pavement crack detection
Narges Kheradmandi, Vida Mehranfar
Construction and Building Materials (2022) Vol. 321, pp. 126162-126162
Closed Access | Times Cited: 234
Review of Pavement Defect Detection Methods
Wenming Cao, Qifan Liu, Zhiquan He
IEEE Access (2020) Vol. 8, pp. 14531-14544
Open Access | Times Cited: 227
Performance Evaluation of Deep CNN-Based Crack Detection and Localization Techniques for Concrete Structures
Luqman Ali, Fady Alnajjar, Hamad Al Jassmi, et al.
Sensors (2021) Vol. 21, Iss. 5, pp. 1688-1688
Open Access | Times Cited: 213
The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis
Yue Hou, Qiuhan Li, Chen Zhang, et al.
Engineering (2020) Vol. 7, Iss. 6, pp. 845-856
Open Access | Times Cited: 211
Detection of concealed cracks from ground penetrating radar images based on deep learning algorithm
Shuwei Li, Xingyu Gu, Xiangrong Xu, et al.
Construction and Building Materials (2020) Vol. 273, pp. 121949-121949
Closed Access | Times Cited: 199
A cost effective solution for pavement crack inspection using cameras and deep neural networks
Qipei Mei, Mustafa Gül
Construction and Building Materials (2020) Vol. 256, pp. 119397-119397
Closed Access | Times Cited: 189
A research on an improved Unet-based concrete crack detection algorithm
Lingxin Zhang, Junkai Shen, Baijie Zhu
Structural Health Monitoring (2020) Vol. 20, Iss. 4, pp. 1864-1879
Closed Access | Times Cited: 174
Computer vision framework for crack detection of civil infrastructure—A review
Dihao Ai, Guiyuan Jiang, Siew-Kei Lam, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105478-105478
Closed Access | Times Cited: 151
Deep convolution neural network-based transfer learning method for civil infrastructure crack detection
Qiaoning Yang, Weimin Shi, Juan Chen, et al.
Automation in Construction (2020) Vol. 116, pp. 103199-103199
Closed Access | Times Cited: 150
Automated pixel-level pavement distress detection based on stereo vision and deep learning
Jinchao Guan, Xu Yang, Ling Ding, et al.
Automation in Construction (2021) Vol. 129, pp. 103788-103788
Closed Access | Times Cited: 136
Pavement crack detection based on transformer network
Feng Guo, Yu Qian, Jian Liu, et al.
Automation in Construction (2022) Vol. 145, pp. 104646-104646
Closed Access | Times Cited: 130
Machine learning techniques for pavement condition evaluation
Nima Sholevar, Amir Golroo, Sahand Roghani Esfahani
Automation in Construction (2022) Vol. 136, pp. 104190-104190
Closed Access | Times Cited: 122
UNet-based model for crack detection integrating visual explanations
Fangyu Liu, Linbing Wang
Construction and Building Materials (2022) Vol. 322, pp. 126265-126265
Closed Access | Times Cited: 110
Review on computer vision-based crack detection and quantification methodologies for civil structures
Jianghua Deng, Amardeep Singh, Yiyi Zhou, et al.
Construction and Building Materials (2022) Vol. 356, pp. 129238-129238
Closed Access | Times Cited: 108
CrackFormer: Transformer Network for Fine-Grained Crack Detection
Huajun Liu, Xiangyu Miao, Christoph Mertz, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021), pp. 3763-3772
Closed Access | Times Cited: 103
A Comprehensive Review of Deep Learning-Based Crack Detection Approaches
Younes Hamishebahar, Hong Guan, Stephen So, et al.
Applied Sciences (2022) Vol. 12, Iss. 3, pp. 1374-1374
Open Access | Times Cited: 93
Automatic classification of asphalt pavement cracks using a novel integrated generative adversarial networks and improved VGG model
Yun Que, Yi Dai, Xue Ji, et al.
Engineering Structures (2023) Vol. 277, pp. 115406-115406
Closed Access | Times Cited: 88
YOLOv5s-M: A deep learning network model for road pavement damage detection from urban street-view imagery
Miao Ren, Xianfeng Zhang, Xiao Chen, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 120, pp. 103335-103335
Open Access | Times Cited: 52
A deeper generative adversarial network for grooved cement concrete pavement crack detection
Jingtao Zhong, Ju Huyan, Weiguang Zhang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 119, pp. 105808-105808
Closed Access | Times Cited: 51
Computer Vision Applications in Intelligent Transportation Systems: A Survey
Esma Dilek, Murat Dener
Sensors (2023) Vol. 23, Iss. 6, pp. 2938-2938
Open Access | Times Cited: 50
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