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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:

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

Showing 1-25 of 465 citing articles:

Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Arman Malekloo, Ekin Özer, Mohammad AlHamaydeh, et al.
Structural Health Monitoring (2021) Vol. 21, Iss. 4, pp. 1906-1955
Open Access | Times Cited: 320
Vibration feature extraction using signal processing techniques for structural health monitoring: A review
Chunwei Zhang, Asma Alsadat Mousavi, Sami F. Masri, et al.
Mechanical Systems and Signal Processing (2022) Vol. 177, pp. 109175-109175
Closed Access | Times Cited: 213
DenseSPH-YOLOv5: An automated damage detection model based on DenseNet and Swin-Transformer prediction head-enabled YOLOv5 with attention mechanism
Arunabha M. Roy, Jayabrata Bhaduri
Advanced Engineering Informatics (2023) Vol. 56, pp. 102007-102007
Closed Access | Times Cited: 152
Three decades of statistical pattern recognition paradigm for SHM of bridges
Elói Figueiredo, James Brownjohn
Structural Health Monitoring (2022) Vol. 21, Iss. 6, pp. 3018-3054
Open Access | Times Cited: 137
Recent trends in smartphone-based detection for biomedical applications: a review
Soumyabrata Banik, Sindhoora Kaniyala Melanthota, Arbaaz, et al.
Analytical and Bioanalytical Chemistry (2021) Vol. 413, Iss. 9, pp. 2389-2406
Open Access | Times Cited: 128
Vision transformer-based autonomous crack detection on asphalt and concrete surfaces
Elyas Asadi Shamsabadi, Chang Xu, Aravinda S. Rao, et al.
Automation in Construction (2022) Vol. 140, pp. 104316-104316
Closed Access | Times Cited: 128
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
3D vision technologies for a self-developed structural external crack damage recognition robot
Kewei Hu, Zheng Chen, Hanwen Kang, et al.
Automation in Construction (2024) Vol. 159, pp. 105262-105262
Closed Access | Times Cited: 104
A review of machine learning methods applied to structural dynamics and vibroacoustic
Barbara Zaparoli Cunha, Christophe Droz, Abdelmalek Zine, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110535-110535
Open Access | Times Cited: 72
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 Data Management and Visualization Techniques for Structural Health Monitoring Using BIM and Virtual or Augmented Reality
Ayan Sadhu, Jack E. Peplinski, Ali Mohammadkhorasani, et al.
Journal of Structural Engineering (2022) Vol. 149, Iss. 1
Closed Access | Times Cited: 71
Application of drones in the architecture, engineering, and construction (AEC) industry
Janet Mayowa Nwaogu, Yang Yang, Albert P.C. Chan, et al.
Automation in Construction (2023) Vol. 150, pp. 104827-104827
Closed Access | Times Cited: 71
Unsupervised Learning Methods for Data-Driven Vibration-Based Structural Health Monitoring: A Review
Kareem Eltouny, Mohamed Gomaa, Xiao Liang
Sensors (2023) Vol. 23, Iss. 6, pp. 3290-3290
Open Access | Times Cited: 61
A Systematic Review of Optimization Algorithms for Structural Health Monitoring and Optimal Sensor Placement
Sahar Hassani, Ulrike Dackermann
Sensors (2023) Vol. 23, Iss. 6, pp. 3293-3293
Open Access | Times Cited: 57
Lightweight semantic segmentation of complex structural damage recognition for actual bridges
Yang Xu, Yunlei Fan, Hui Li
Structural Health Monitoring (2023) Vol. 22, Iss. 5, pp. 3250-3269
Closed Access | Times Cited: 47
Damage identification of steel bridge based on data augmentation and adaptive optimization neural network
Minshui Huang, Jianwei Zhang, Jun Li, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 24
A novel unsupervised deep learning approach for vibration-based damage diagnosis using a multi-head self-attention LSTM autoencoder
Shayan Ghazimoghadam, S.A.A. Hosseinzadeh
Measurement (2024) Vol. 229, pp. 114410-114410
Closed Access | Times Cited: 18
Camera-Based Real-Time Damage Identification of Building Structures through Deep Learning
Sajad Javadinasab Hormozabad, Alejandro Palacio‐Betancur, Mariantonieta Gutiérrez Soto
Journal of structural design and construction practice. (2025) Vol. 30, Iss. 2
Closed Access | Times Cited: 1
Assessing uncertainty in image-based monitoring: addressing false positives, false negatives, and base rate bias in structural health evaluation
Vagelis Plevris
Stochastic Environmental Research and Risk Assessment (2025)
Open Access | Times Cited: 1
Data–model Fusion Methods and Applications toward Smart Manufacturing and Digital Engineering
Fei Tao, Yilin Li, Yupeng Wei, et al.
Engineering (2025)
Open Access | Times Cited: 1
Monitoring of transport infrastructure exposed to multiple hazards: a roadmap for building resilience
Dimitra V. Achillopoulou, Stergios Α. Mitoulis, Sotirios Argyroudis, et al.
The Science of The Total Environment (2020) Vol. 746, pp. 141001-141001
Open Access | Times Cited: 94
Machine learning applied to the design and inspection of reinforced concrete bridges: Resilient methods and emerging applications
Weiying Fan, Yao Chen, Jiaqiang Li, et al.
Structures (2021) Vol. 33, pp. 3954-3963
Closed Access | Times Cited: 88
Autonomous damage recognition in visual inspection of laminated composite structures using deep learning
Sakineh Fotouhi, Farzad Pashmforoush, Mahdi Bodaghi, et al.
Composite Structures (2021) Vol. 268, pp. 113960-113960
Open Access | Times Cited: 81
Explainable 1-D convolutional neural network for damage detection using Lamb wave
P. C. Pandey, Akshay Rai, Mira Mitra
Mechanical Systems and Signal Processing (2021) Vol. 164, pp. 108220-108220
Closed Access | Times Cited: 81
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
Huachen Jiang, Chunfeng Wan, Kang Yang, et al.
Structural Health Monitoring (2021) Vol. 21, Iss. 3, pp. 1093-1109
Closed Access | Times Cited: 76
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