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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:

Machine learning-based real-time visible fatigue crack growth detection
Le Zhang, Zhichen Wang, Lei Wang, et al.
Digital Communications and Networks (2021) Vol. 7, Iss. 4, pp. 551-558
Open Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications
Dongwhi Choi, Young‐Hoon Lee, Zong‐Hong Lin, et al.
ACS Nano (2023) Vol. 17, Iss. 12, pp. 11087-11219
Open Access | Times Cited: 268
Fatigue modeling using neural networks: A comprehensive review
Jie Chen, Yongming Liu
Fatigue & Fracture of Engineering Materials & Structures (2022) Vol. 45, Iss. 4, pp. 945-979
Open Access | Times Cited: 152
Physics-guided machine learning frameworks for fatigue life prediction of AM materials
Lanyi Wang, Shun‐Peng Zhu, Changqi Luo, et al.
International Journal of Fatigue (2023) Vol. 172, pp. 107658-107658
Closed Access | Times Cited: 65
Task-aware meta-learning paradigm for universal structural damage segmentation using limited images
Yang Xu, Yunlei Fan, Yuequan Bao, et al.
Engineering Structures (2023) Vol. 284, pp. 115917-115917
Closed Access | Times Cited: 41
Stiff and tough PDMS-MMT layered nanocomposites visualized by AIE luminogens
Jingsong Peng, Antoni P. Tomsia, Lei Jiang, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 95
Machine learning based very-high-cycle fatigue life prediction of AlSi10Mg alloy fabricated by selective laser melting
Tao Shi, Jingyu Sun, Jianghua Li, et al.
International Journal of Fatigue (2023) Vol. 171, pp. 107585-107585
Closed Access | Times Cited: 39
Augmented reality-computer vision combination for automatic fatigue crack detection and localization
Ali Mohammadkhorasani, Kaveh Malek, Rushil Mojidra, et al.
Computers in Industry (2023) Vol. 149, pp. 103936-103936
Closed Access | Times Cited: 26
Cascade refinement extraction network with active boundary loss for segmentation of concrete cracks from high-resolution images
Lu Deng, Huaqing Yuan, Lizhi Long, et al.
Automation in Construction (2024) Vol. 162, pp. 105410-105410
Open Access | Times Cited: 9
Smart mechanoluminescent phosphors: A review of zinc sulfide‐based materials for advanced mechano‐optical applications
Zefeng Huang, Li Xu, Tianlong Liang, et al.
Deleted Journal (2024) Vol. 2, Iss. 3
Open Access | Times Cited: 9
Optimum feature selection for the supervised damage classification of an operating wind turbine blade
Mohadeseh Ashkarkalaei, Ramin Ghiasi, Vikram Pakrashi, et al.
Structural Health Monitoring (2025)
Closed Access | Times Cited: 1
Entropy-based redundancy analysis and information screening
Yang Li, Jiachen Yang, Jiabao Wen
Digital Communications and Networks (2021) Vol. 9, Iss. 5, pp. 1061-1069
Open Access | Times Cited: 52
Prediction of fatigue crack growth rate in aircraft aluminum alloys using optimized neural networks
Hassaan Bin Younis, Khurram Kamal, Muhammad Fahad Sheikh, et al.
Theoretical and Applied Fracture Mechanics (2021) Vol. 117, pp. 103196-103196
Open Access | Times Cited: 48
A novel information entropy approach for crack monitoring leveraging nondestructive evaluation sensing
Sarah Malik, Antonios Kontsos
Mechanical Systems and Signal Processing (2024) Vol. 214, pp. 111207-111207
Closed Access | Times Cited: 6
Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder–Decoder Network
Chuan‐Zhi Dong, Liangding Li, Jin Yan, et al.
Sensors (2021) Vol. 21, Iss. 12, pp. 4135-4135
Open Access | Times Cited: 35
Machine Learning Techniques for Structural Health Monitoring of Concrete Structures: A Systematic Review
P. Padmapoorani, S. Senthilkumar, R. Mohanraj
Iranian Journal of Science and Technology Transactions of Civil Engineering (2023) Vol. 47, Iss. 4, pp. 1919-1931
Closed Access | Times Cited: 15
Principles, properties, and sensing applications of mechanoluminescence materials
Junwen Yu, Q. Niu, Yun Liu, et al.
Journal of Materials Chemistry C (2023) Vol. 11, Iss. 43, pp. 14968-15000
Closed Access | Times Cited: 15
A machine learning based approach with an augmented dataset for fatigue life prediction of additively manufactured Ti-6Al-4V samples
Jan Horňas, Jiří Běhal, Petr Homola, et al.
Engineering Fracture Mechanics (2023) Vol. 293, pp. 109709-109709
Open Access | Times Cited: 15
Hybrid 3D printed three-axis force sensor aided by machine learning decoupling
Guotao Liu, Peishi Yu, Yin Tao, et al.
International Journal of Smart and Nano Materials (2024) Vol. 15, Iss. 2, pp. 261-278
Open Access | Times Cited: 5
Fast Reverse Design of 4D‐Printed Voxelized Composite Structures Using Deep Learning and Evolutionary Algorithm
Mengtao Wang, Zaiyang Liu, Hidemitsu Furukawa, et al.
Advanced Science (2025)
Open Access
Multifactorial prediction of corrosion fatigue crack growth in aluminum alloys using physics-informed neural networks
Tianhao Huang, Xueyuan Li, Yongzhen Zhang, et al.
Engineering Failure Analysis (2025), pp. 109521-109521
Closed Access
Machine learning-based prediction of hydrogen-assisted fatigue crack growth rate in Cr–Mo steel
Jiangchuan Hu, Kai Ma, Zhenquan Zhang, et al.
International Journal of Hydrogen Energy (2025) Vol. 122, pp. 1-11
Closed Access
A study on depth classification of defects by machine learning based on hyper-parameter search
Haoze Chen, Zhijie Zhang, Wuliang Yin, et al.
Measurement (2021) Vol. 189, pp. 110660-110660
Closed Access | Times Cited: 31
Fracture process simulation and crack resistance behavior analysis of transition-layer ceramic coating based on real image reconstruction model
Xuan He, Peng Song, Taihong Huang, et al.
Surfaces and Interfaces (2024) Vol. 46, pp. 104003-104003
Closed Access | Times Cited: 4
MPSU-Net: Quantitative interpretation algorithm for road cracks based on multiscale feature fusion and superimposed U-Net
Ban Wang, J.N. Li, Changlu Dai, et al.
Digital Signal Processing (2024) Vol. 153, pp. 104598-104598
Closed Access | Times Cited: 4
Transfer learned deep feature based crack detection using support vector machine: a comparative study
K. S. Bhalaji Kharthik, Edeh Michael Onyema, Saurav Mallik, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
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