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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:

Exploring the Detection Accuracy of Concrete Cracks Using Various CNN Models
Mohammed Ameen Mohammed, Zheng Han, Yange Li
Advances in Materials Science and Engineering (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 18

Showing 18 citing articles:

Structural Damage Identification Using Ensemble Deep Convolutional Neural Network Models
Mohammad Sadegh Barkhordari, Danial Jahed Armaghani, Panagiotis G. Asteris
Computer Modeling in Engineering & Sciences (2022) Vol. 134, Iss. 2, pp. 835-855
Open Access | Times Cited: 59
Towards sustainable construction: Machine learning based predictive models for strength and durability characteristics of blended cement concrete
Majid Khan, Muhammad Faisal Javed
Materials Today Communications (2023) Vol. 37, pp. 107428-107428
Closed Access | Times Cited: 40
Computing the characteristics of defects in wooden structures using image processing and CNN
Rana Ehtisham, Waqas Qayyum, Charles V. Camp, et al.
Automation in Construction (2023) Vol. 158, pp. 105211-105211
Closed Access | Times Cited: 28
Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open- Access Papers
Nils Hütten, Miguel Alves Gomes, Florian Hölken, et al.
Applied System Innovation (2024) Vol. 7, Iss. 1, pp. 11-11
Open Access | Times Cited: 13
MultiScaleCrackNet: A parallel multiscale deep CNN architecture for concrete crack classification
R. Newlin Shebiah, S. Arivazhagan
Expert Systems with Applications (2024) Vol. 249, pp. 123658-123658
Closed Access | Times Cited: 11
Research on concrete dam crack identification and localisation based on CDI-AR convolutional neural network
Kui Wang, Zhu Linchen, Mingjie Zhao, et al.
Nondestructive Testing And Evaluation (2025), pp. 1-22
Closed Access
Hyperparameter Optimization and Importance Ranking in Deep Learning–Based Crack Segmentation
Carlos Canchila, Shanglian Zhou, Wei Song
Journal of Computing in Civil Engineering (2023) Vol. 38, Iss. 2
Closed Access | Times Cited: 10
Dam Crack Image Detection Model on Feature Enhancement and Attention Mechanism
Guoyan Xu, Xu Han, Yuwei Zhang, et al.
Water (2022) Vol. 15, Iss. 1, pp. 64-64
Open Access | Times Cited: 14
Deep CNN-based concrete cracks identification and quantification using image processing techniques
Madhuri Gonthina, Renuka Chamata, Jhanshi Duppalapudi, et al.
Asian Journal of Civil Engineering (2022) Vol. 24, Iss. 3, pp. 727-740
Closed Access | Times Cited: 11
Analytical Models of Concrete Fatigue: A State-of-the-Art Review
Xiaoli Wei, D.A. Makhloof, Xiaodan Ren
Computer Modeling in Engineering & Sciences (2022) Vol. 134, Iss. 1, pp. 9-34
Open Access | Times Cited: 9
A Lightweight CNN-Based Vision System for Concrete Crack Detection on a Low-Power Embedded Microcontroller Platform
Laura Falaschetti, Mattia Beccerica, Giorgio Biagetti, et al.
Procedia Computer Science (2022) Vol. 207, pp. 3948-3956
Open Access | Times Cited: 8
End-to-end semi-supervised deep learning model for surface crack detection of infrastructures
Mohammed Ameen Mohammed, Zheng Han, Yange Li, et al.
Frontiers in Materials (2022) Vol. 9
Open Access | Times Cited: 8
INTELLIGENT DETECTION OF CONCRETE APPARENT DEFECTS BASED ON A DEEP LEARNING - LITERATURE REVIEW, KNOWLEDGE GAPS AND FUTURE DEVELOPMENTS
Jiading Zhang
Ceramics - Silikaty (2024)
Open Access | Times Cited: 1
Utilizing pretrained convolutional neural networks for crack detection and geometric feature recognition in concrete surface images
Miao Su, Jingkai Wan, Qilin Zhou, et al.
Journal of Building Engineering (2024), pp. 111386-111386
Closed Access | Times Cited: 1
Advancements in Machine Learning-Based Condition Monitoring for Crack Detection in Windmill Blades: A Comprehensive Review
K. Ashwitha, M. C. Kiran, Surendra Shetty, et al.
Archives of Computational Methods in Engineering (2024)
Closed Access
Enhanced pavement crack segmentation with minimal labeled data: a triplet attention teacher-student framework
Mohammed Ameen Mohammed, Zheng Han, Yange Li, et al.
International Journal of Pavement Engineering (2024) Vol. 25, Iss. 1
Closed Access
Finding Concrete Cracks in a Building using Improved Deep Learning Algorithms
V. Devisurya, Joseph N. Paulson, M Seshadhri, et al.
(2023), pp. 332-339
Closed Access
Concrete Crack Identification Using Convolution Neural Network
Atul Kumar Uttam
(2023), pp. 914-917
Closed Access
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