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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:

Structural damage detection and localization using decision tree ensemble and vibration data
Giulio Mariniello, Tommaso Pastore, Costantino Menna, et al.
Computer-Aided Civil and Infrastructure Engineering (2020) Vol. 36, Iss. 9, pp. 1129-1149
Closed Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices
Arash Teymori Gharah Tapeh, M.Z. Naser
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 1, pp. 115-159
Closed Access | Times Cited: 156
State-of-the-art review on advancements of data mining in structural health monitoring
Meisam Gordan, Saeed-Reza Sabbagh-Yazdi, Zubaidah Ismail, et al.
Measurement (2022) Vol. 193, pp. 110939-110939
Closed Access | Times Cited: 126
Vision-based real-time structural vibration measurement through deep-learning-based detection and tracking methods
Xiao Pan, T.Y. Yang, Yifei Xiao, et al.
Engineering Structures (2023) Vol. 281, pp. 115676-115676
Closed Access | Times Cited: 90
State of the art in structural health monitoring of offshore and marine structures
Hadi Pezeshki, Hojjat Adeli, Dimitrios G. Pavlou, et al.
Proceedings of the Institution of Civil Engineers - Maritime Engineering (2023) Vol. 176, Iss. 2, pp. 89-108
Open Access | Times Cited: 85
Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art
Raffaele Zinno, Sina Shaffiee Haghshenas, Giuseppe Guido, et al.
IEEE Access (2022) Vol. 10, pp. 88058-88078
Open Access | Times Cited: 72
A review of the application of the simulated annealing algorithm in structural health monitoring (1995-2021)
Parsa Ghannadi, Seyed Sina Kourehli, Seyedali Mirjalili
Frattura ed Integrità Strutturale (2023) Vol. 17, Iss. 64, pp. 51-76
Open Access | Times Cited: 46
Convolutional neural networks (CNNs)-based multi-category damage detection and recognition of high-speed rail (HSR) reinforced concrete (RC) bridges using test images
Lingkun Chen, Wenxin Chen, Lu Wang, et al.
Engineering Structures (2022) Vol. 276, pp. 115306-115306
Closed Access | Times Cited: 61
Multicategory damage detection and safety assessment of post‐earthquake reinforced concrete structures using deep learning
Dujian Zou, Ming Zhang, Zhilin Bai, et al.
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 9, pp. 1188-1204
Closed Access | Times Cited: 60
SHM under varying environmental conditions: an approach based on model order reduction and deep learning
Matteo Torzoni, Luca Rosafalco, Andrea Manzoni, et al.
Computers & Structures (2022) Vol. 266, pp. 106790-106790
Closed Access | Times Cited: 43
Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results
Tatsuro Yamane, Pang-jo CHUN, Ji Dang, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 38, Iss. 17, pp. 2391-2407
Open Access | Times Cited: 32
Damage detection of structures based on wavelet analysis using improved AlexNet
Hessam Amanollah, Arghavan Asghari, ‪Mohammadreza Mashayekhi, et al.
Structures (2023) Vol. 56, pp. 105019-105019
Closed Access | Times Cited: 22
Data-driven machine learning for pattern recognition and detection of loosening torque in bolted joints
Jefferson da Silva Coelho, Marcela Machado, Maciej Dutkiewicz, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 2
Open Access | Times Cited: 9
Deep learning-based bridge damage cause estimation from multiple images using visual question answering
Tatsuro Yamane, Pang-jo CHUN, Ji Dang, et al.
Structure and Infrastructure Engineering (2024), pp. 1-14
Open Access | Times Cited: 9
A hybrid GRU and LSTM-based deep learning approach for multiclass structural damage identification using dynamic acceleration data
T. K. Das, Shyamal Guchhait
Engineering Failure Analysis (2025), pp. 109259-109259
Closed Access | Times Cited: 1
Improved damage assessment of bridges using advanced signal processing techniques of CEEMDAN-EWT and Kernal PCA
Hayati Abdullah, Muhammad Usman Hanif, Muhammad Usman Hassan, et al.
Engineering Structures (2025) Vol. 329, pp. 119774-119774
Open Access | Times Cited: 1
Deep generative Bayesian optimization for sensor placement in structural health monitoring
Seyed Omid Sajedi, Xiao Liang
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 37, Iss. 9, pp. 1109-1127
Closed Access | Times Cited: 48
Image‐based monitoring of bolt loosening through deep‐learning‐based integrated detection and tracking
Xiao Pan, T.Y. Yang
Computer-Aided Civil and Infrastructure Engineering (2021) Vol. 37, Iss. 10, pp. 1207-1222
Open Access | Times Cited: 44
Structural damage detection framework based on graph convolutional network directly using vibration data
Viet-Hung Dang, Tien-Chuong Vu, Ba-Duan Nguyen, et al.
Structures (2022) Vol. 38, pp. 40-51
Closed Access | Times Cited: 36
Structural damage detection based on convolutional neural networks and population of bridges
Shuai Teng, Xuedi Chen, Gongfa Chen, et al.
Measurement (2022) Vol. 202, pp. 111747-111747
Closed Access | Times Cited: 35
Active learning structural model updating of a multisensory system based on Kriging method and Bayesian inference
Ye Yuan, F.T.K. Au, Dong Yang, et al.
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 38, Iss. 3, pp. 353-371
Closed Access | Times Cited: 33
The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020)
Parsa Ghannadi, Seyed Sina Kourehli, Seyedali Mirjalili
Frattura ed Integrità Strutturale (2022) Vol. 16, Iss. 62, pp. 460-489
Open Access | Times Cited: 30
Current and future role of data fusion and machine learning in infrastructure health monitoring
Hao Wang, Giorgio Barone, Alister Smith
Structure and Infrastructure Engineering (2023) Vol. 20, Iss. 12, pp. 1853-1882
Open Access | Times Cited: 21
An automated vibration-based structural damage localization strategy using filter-type feature selection
Victor Alves, Alexandre Cury
Mechanical Systems and Signal Processing (2023) Vol. 190, pp. 110145-110145
Closed Access | Times Cited: 20
Damage detection in power transmission towers using machine learning algorithms
Mehdi Kouchaki, Mojtaba Salkhordeh, ‪Mohammadreza Mashayekhi, et al.
Structures (2023) Vol. 56, pp. 104980-104980
Closed Access | Times Cited: 17
Structural health monitoring of civil structures: A diagnostic framework powered by deep metric learning
Matteo Torzoni, Andrea Manzoni, Stefano Mariani
Computers & Structures (2022) Vol. 271, pp. 106858-106858
Closed Access | Times Cited: 27
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