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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 Features Extracted by Convolutional Neural Networks from Mode Shapes
Kefeng Zhong, Shuai Teng, Gen Liu, et al.
Applied Sciences (2020) Vol. 10, Iss. 12, pp. 4247-4247
Open Access | Times Cited: 22

Showing 22 citing articles:

The Current Development of Structural Health Monitoring for Bridges: A Review
Z.C. Deng, Minshui Huang, Neng Wan, et al.
Buildings (2023) Vol. 13, Iss. 6, pp. 1360-1360
Open Access | Times Cited: 96
Structural damage identification using strain mode differences by the iFEM based on the convolutional neural network (CNN)
Mengying Li, Dawei Jia, Ziyan Wu, et al.
Mechanical Systems and Signal Processing (2021) Vol. 165, pp. 108289-108289
Closed Access | Times Cited: 69
Concrete Crack Detection Based on Well-Known Feature Extractor Model and the YOLO_v2 Network
Shuai Teng, Zongchao Liu, Gongfa Chen, et al.
Applied Sciences (2021) Vol. 11, Iss. 2, pp. 813-813
Open Access | Times Cited: 63
Review of Machine-Learning Techniques Applied to Structural Health Monitoring Systems for Building and Bridge Structures
Alain Gomez-Cabrera, Ponciano Jorge Escamilla-Ambrosio
Applied Sciences (2022) Vol. 12, Iss. 21, pp. 10754-10754
Open Access | Times Cited: 57
Multi-Sensor and Decision-Level Fusion-Based Structural Damage Detection Using a One-Dimensional Convolutional Neural Network
Shuai Teng, Gongfa Chen, Zongchao Liu, et al.
Sensors (2021) Vol. 21, Iss. 12, pp. 3950-3950
Open Access | Times Cited: 48
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
Deep Learning-Enabled Health Assessment for Sustainable Maintenance of Existing Concrete Structures: A Review
Pankaj Panwar, K. L. Goyal, Jatin Kumar Shandilya
Springer tracts in civil engineering (2025), pp. 93-121
Closed Access
Two-dimensional convolutional neural network and transfer learning-based multi-stage structural damage quantification using vibration data
Ma Shenglan, Xu Miaoyu, Yuhao Liu, et al.
Structure and Infrastructure Engineering (2025), pp. 1-18
Closed Access
Uncover Hidden Physical Information of Soft Matter by Observing Large Deformation
Huanyu Yang, Yiwei Cheng, Penghui Zhao, et al.
Advanced Science (2025)
Open Access
Vibration-based structural damage detection using 1-D convolutional neural network and transfer learning
Shuai Teng, Gongfa Chen, Zhaocheng Yan, et al.
Structural Health Monitoring (2022) Vol. 22, Iss. 4, pp. 2888-2909
Closed Access | Times Cited: 17
Comparative Effectiveness of Data Augmentation Using Traditional Approaches versus StyleGANs in Automated Sewer Defect Detection
Qianqian Zhou, Zuxiang Situ, Shuai Teng, et al.
Journal of Water Resources Planning and Management (2023) Vol. 149, Iss. 9
Closed Access | Times Cited: 9
Data-driven approach for AI-based crack detection: techniques, challenges, and future scope
Priti Chakurkar, Deepali Vora, Shruti Patil, et al.
Frontiers in Sustainable Cities (2023) Vol. 5
Open Access | Times Cited: 8
Progress of Atomic Layer Deposition and Molecular Layer Deposition in the Development of All‐Solid‐State Lithium Batteries
Yu Su, Jialiang Hao, Xiangsi Liu, et al.
Batteries & Supercaps (2022) Vol. 6, Iss. 1
Closed Access | Times Cited: 10
An Inversion Algorithm for the Dynamic Modulus of Concrete Pavement Structures Based on a Convolutional Neural Network
Gongfa Chen, Xuedi Chen, Linqing Yang, et al.
Applied Sciences (2023) Vol. 13, Iss. 2, pp. 1192-1192
Open Access | Times Cited: 5
Structural damage detection based on decision-level fusion with multi-vibration signals
Jiqiao Zhang, Zihan Jin, Shuai Teng, et al.
Measurement Science and Technology (2022) Vol. 33, Iss. 10, pp. 105112-105112
Closed Access | Times Cited: 8
Flow Velocity Computation in Solid–Liquid Two-Phase Flow by a Hybrid Network CNN–RKSVM
Kun Li, Shihong Yue, Liping Liu
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4611-4611
Open Access | Times Cited: 1
Structural Damage Detection Using Convolutional Neural Networks Based on Modal Strain Energy and Population of Structures
Jiqiao Zhang, Zihan Jin, Shuai Teng, et al.
International Journal of Computational Methods (2022) Vol. 20, Iss. 03
Closed Access | Times Cited: 5
Identification of Mode Shapes of a Composite Cylinder Using Convolutional Neural Networks
Bartosz Miller, Leonard Ziemiański
Materials (2021) Vol. 14, Iss. 11, pp. 2801-2801
Open Access | Times Cited: 7
Detection of Material Degradation of a Composite Cylinder Using Mode Shapes and Convolutional Neural Networks
Bartosz Miller, Leonard Ziemiański
Materials (2021) Vol. 14, Iss. 21, pp. 6686-6686
Open Access | Times Cited: 6
Sensitivity Analyses of Structural Damage Indicators and ‎Experimental Validations
Jiqiao Zhang, Zhiqiang Teng, Xiaojian Xu, et al.
HAL (Le Centre pour la Communication Scientifique Directe) (2020)
Closed Access | Times Cited: 2
Femoral Fracture Assessment Using Acceleration Signals Combined with Convolutional Neural Network
Jiqiao Zhang, Silang Zhu, Zihan Jin, et al.
Journal of Vibration Engineering & Technologies (2023) Vol. 12, Iss. 3, pp. 4987-5005
Closed Access
Machine Learning Vibration-Based Damage Detection and Early-Developed Damage Indicators
Renan Rocha Ribeiro, Luís Augusto Conte Mendes Veloso, Rodrigo de Melo Lameiras
Conference proceedings of the Society for Experimental Mechanics (2021), pp. 23-32
Closed Access
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