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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:

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring
Billie F. Spencer, Vedhus Hoskere, Yasutaka Narazaki
Engineering (2019) Vol. 5, Iss. 2, pp. 199-222
Open Access | Times Cited: 851

Showing 1-25 of 851 citing articles:

Roles of artificial intelligence in construction engineering and management: A critical review and future trends
Yue Pan, Limao Zhang
Automation in Construction (2020) Vol. 122, pp. 103517-103517
Closed Access | Times Cited: 741
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: 523
Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review
Mohsen Azimi, Armin Dadras Eslamlou, Gökhan Pekcan
Sensors (2020) Vol. 20, Iss. 10, pp. 2778-2778
Open Access | Times Cited: 465
Machine learning for structural engineering: A state-of-the-art review
Huu‐Tai Thai
Structures (2022) Vol. 38, pp. 448-491
Closed Access | Times Cited: 377
Image-based concrete crack detection in tunnels using deep fully convolutional networks
Yupeng Ren, Jisheng Huang, Zhiyou Hong, et al.
Construction and Building Materials (2019) Vol. 234, pp. 117367-117367
Closed Access | Times Cited: 375
Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning
Dimitrios Dais, İhsan Engin Bal, Eleni Smyrou, et al.
Automation in Construction (2021) Vol. 125, pp. 103606-103606
Open Access | Times Cited: 303
Structural health monitoring of civil engineering structures by using the internet of things: A review
Mayank Mishra, Paulo B. Lourénço, G. V. Ramana
Journal of Building Engineering (2022) Vol. 48, pp. 103954-103954
Closed Access | Times Cited: 300
A systematic review of convolutional neural network-based structural condition assessment techniques
Sandeep Sony, Kyle Dunphy, Ayan Sadhu, et al.
Engineering Structures (2020) Vol. 226, pp. 111347-111347
Closed Access | Times Cited: 292
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: 266
Extraction of mechanical properties of materials through deep learning from instrumented indentation
Lu Lu, Ming Dao, Punit Kumar, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 13, pp. 7052-7062
Open Access | Times Cited: 264
A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges
Patrick McEnroe, Shen Wang, Madhusanka Liyanage
IEEE Internet of Things Journal (2022) Vol. 9, Iss. 17, pp. 15435-15459
Open Access | Times Cited: 235
Machine learning paradigm for structural health monitoring
Yuequan Bao, Hui Li
Structural Health Monitoring (2020) Vol. 20, Iss. 4, pp. 1353-1372
Closed Access | Times Cited: 220
Digital technologies can enhance climate resilience of critical infrastructure
Sotirios Argyroudis, Stergios Α. Mitoulis, Eleni Chatzi, et al.
Climate Risk Management (2021) Vol. 35, pp. 100387-100387
Open Access | Times Cited: 186
A scientometric analysis and critical review of computer vision applications for construction
Pablo Martı́nez, Mohamed Al‐Hussein, Rafiq Ahmad
Automation in Construction (2019) Vol. 107, pp. 102947-102947
Closed Access | Times Cited: 180
Pavement distress detection using convolutional neural networks with images captured via UAV
Junqing Zhu, Jingtao Zhong, Tao Ma, et al.
Automation in Construction (2021) Vol. 133, pp. 103991-103991
Closed Access | Times Cited: 177
Surface crack detection using deep learning with shallow CNN architecture for enhanced computation
Bubryur Kim, N. Yuvaraj, K. R. Sri Preethaa, et al.
Neural Computing and Applications (2021) Vol. 33, Iss. 15, pp. 9289-9305
Closed Access | Times Cited: 161
Computer vision applications in construction: Current state, opportunities & challenges
Suman Paneru, Idris Jeelani
Automation in Construction (2021) Vol. 132, pp. 103940-103940
Open Access | Times Cited: 161
Towards next generation design of sustainable, durable, multi-hazard resistant, resilient, and smart civil engineering structures
Hong Hao, Kaiming Bi, Wensu Chen, et al.
Engineering Structures (2022) Vol. 277, pp. 115477-115477
Closed Access | Times Cited: 158
Machine learning for structural health monitoring: challenges and opportunities
Fuh‐Gwo Yuan, Sakib Ashraf Zargar, Qiuyi Chen, et al.
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2018 (2020)
Open Access | Times Cited: 143
A Decade of Modern Bridge Monitoring Using Terrestrial Laser Scanning: Review and Future Directions
Maria Rashidi, Masoud Mohammadi, Saba Sadeghlou Kivi, et al.
Remote Sensing (2020) Vol. 12, Iss. 22, pp. 3796-3796
Open Access | Times Cited: 141
Acceptance Model of Artificial Intelligence (AI)-Based Technologies in Construction Firms: Applying the Technology Acceptance Model (TAM) in Combination with the Technology–Organisation–Environment (TOE) Framework
Seunguk Na, Seokjae Heo, Sehee Han, et al.
Buildings (2022) Vol. 12, Iss. 2, pp. 90-90
Open Access | Times Cited: 136
A Critical Review on Structural Health Monitoring: Definitions, Methods, and Perspectives
Vahidreza Gharehbaghi, Ehsan Noroozinejad Farsangi, Mohammad Noori, et al.
Archives of Computational Methods in Engineering (2021) Vol. 29, Iss. 4, pp. 2209-2235
Closed Access | Times Cited: 125
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
Automatic image-based brick segmentation and crack detection of masonry walls using machine learning
Dimitrios Loverdos, Vasilis Sarhosis
Automation in Construction (2022) Vol. 140, pp. 104389-104389
Open Access | Times Cited: 98
Intelligent robotic systems for structural health monitoring: Applications and future trends
Yongding Tian, Chao Chen, Kwesi Sagoe–Crentsil, et al.
Automation in Construction (2022) Vol. 139, pp. 104273-104273
Closed Access | Times Cited: 97
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