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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:

Computer Vision-Based Bridge Damage Detection Using Deep Convolutional Networks with Expectation Maximum Attention Module
Wenting Qiao, Biao Ma, Qiangwei Liu, et al.
Sensors (2021) Vol. 21, Iss. 3, pp. 824-824
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

Tiny‐Crack‐Net: A multiscale feature fusion network with attention mechanisms for segmentation of tiny cracks
Hong-Hu Chu, Wei Wang, Lu Deng
Computer-Aided Civil and Infrastructure Engineering (2022) Vol. 37, Iss. 14, pp. 1914-1931
Closed Access | Times Cited: 90
Smart and Automated Infrastructure Management: A Deep Learning Approach for Crack Detection in Bridge Images
Hina Inam, Naeem Ul Islam, Muhammad Usman Akram, et al.
Sustainability (2023) Vol. 15, Iss. 3, pp. 1866-1866
Open Access | Times Cited: 40
Temperature Effect on Vibration Properties and Vibration-Based Damage Identification of Bridge Structures: A Literature Review
Jin Luo, Minshui Huang, Yongzhi Lei
Buildings (2022) Vol. 12, Iss. 8, pp. 1209-1209
Open Access | Times Cited: 50
Semi-supervised learning framework for crack segmentation based on contrastive learning and cross pseudo supervision
Chaoqun Xiang, Vincent J.L. Gan, Guo Jingjing, et al.
Measurement (2023) Vol. 217, pp. 113091-113091
Closed Access | Times Cited: 32
Automated bridge crack evaluation through deep super resolution network-based hybrid image matching
Keunyoung Jang, Hyunjun Jung, Yun‐Kyu An
Automation in Construction (2022) Vol. 137, pp. 104229-104229
Closed Access | Times Cited: 35
The application of deep learning in bridge health monitoring: a literature review
Guo-Qing Zhang, Bin Wang, Jun Li, et al.
Advances in Bridge Engineering (2022) Vol. 3, Iss. 1
Open Access | Times Cited: 29
Improving visual question answering for bridge inspection by pre‐training with external data of image–text pairs
Thannarot Kunlamai, Tatsuro Yamane, Masanori Suganuma, et al.
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 3, pp. 345-361
Open Access | Times Cited: 17
Deep neural networks for crack detection inside structures
Fatahlla Moreh, Hao Lyu, Zarghaam Haider Rizvi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Two-step approach for fatigue crack detection in steel bridges using convolutional neural networks
Said Quqa, Panagiotis Martakis, Artur Movsessian, et al.
Journal of Civil Structural Health Monitoring (2021) Vol. 12, Iss. 1, pp. 127-140
Closed Access | Times Cited: 38
UAV-Driven Structural Crack Detection and Location Determination Using Convolutional Neural Networks
Daegyun Choi, William Bell, Donghoon Kim, et al.
Sensors (2021) Vol. 21, Iss. 8, pp. 2650-2650
Open Access | Times Cited: 35
A review of latest trends in bridge health monitoring
F. Necati Çatbaş, Onur Avcı
Proceedings of the Institution of Civil Engineers - Bridge Engineering (2022) Vol. 176, Iss. 2, pp. 76-91
Closed Access | Times Cited: 21
A Comparative Analysis of Deep Learning Convolutional Neural Network Architectures for Fault Diagnosis of Broken Rotor Bars in Induction Motors
Kevin Barrera, Jordi Burriel-Valencia, Ángel Sapena-Bañó, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8196-8196
Open Access | Times Cited: 12
Modal sensitivity analysis of acoustic metamaterials for structural damage detection
Y. F. Xu, Guoliang Huang
International Journal of Mechanical Sciences (2023) Vol. 259, pp. 108571-108571
Open Access | Times Cited: 11
Research on multi-apparent defects detection of concrete bridges based on YOLOR
Hang Sun, Dewen Lu, Li Xi, et al.
Structures (2024) Vol. 65, pp. 106735-106735
Closed Access | Times Cited: 3
Evolutionary Computation Modelling for Structural Health Monitoring of Critical Infrastructure
Charanjeet Singh Tumrate, Dinesh Kumar Saini, Punit Gupta, et al.
Archives of Computational Methods in Engineering (2022) Vol. 30, Iss. 3, pp. 1479-1493
Closed Access | Times Cited: 15
Convolutional Neural Network for Predicting Failure Type in Concrete Cylinders During Compression Testing
Jose Manuel Palomino Ojeda, Billy Alexis Cayatopa Calderón, Lenin Quiñones Huatangari, et al.
Civil Engineering Journal (2023) Vol. 9, Iss. 9, pp. 2105-2119
Open Access | Times Cited: 8
CrackDenseLinkNet: a deep convolutional neural network for semantic segmentation of cracks on concrete surface images
P. Manjunatha, Sami F. Masri, Aiichiro Nakano, et al.
Structural Health Monitoring (2023) Vol. 23, Iss. 2, pp. 796-817
Closed Access | Times Cited: 7
Application Research of Bridge Damage Detection Based on the Improved Lightweight Convolutional Neural Network Model
Fujun Du, Shuangjian Jiao, Kaili Chu
Applied Sciences (2022) Vol. 12, Iss. 12, pp. 6225-6225
Open Access | Times Cited: 10
Detection of Nut–Bolt Loss in Steel Bridges Using Deep Learning Techniques
Zhijun Li, Kabiru Adamu, Kai Yan, et al.
Sustainability (2022) Vol. 14, Iss. 17, pp. 10837-10837
Open Access | Times Cited: 8
Strategies for improving the detection accuracy of computerized machine vision considering spatial applications
Mincheng Piao, Meng Song
3C TIC Cuadernos de desarrollo aplicados a las TIC (2024) Vol. 13, Iss. 1, pp. 76-94
Open Access | Times Cited: 1
Automated crack identification in structures using acoustic waveforms and deep learning
Mohamed Barbosh, Liangfu Ge, Ayan Sadhu
Journal of Infrastructure Preservation and Resilience (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 1
BD-YOLOv8s: enhancing bridge defect detection with multidimensional attention and precision reconstruction
Wenyuan Xu, Xiang Li, Yongcheng Ji, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
The effects of multidimensional data clustering on the accuracy of virtual in-situ calibration in the photovoltaic/Thermal heat pump system
Jiteng Li, Peng Wang, Tianyi Zhao, et al.
Journal of Building Engineering (2021) Vol. 45, pp. 103500-103500
Closed Access | Times Cited: 11
A concept of an automated damage management for the maintenance of bridge structures in the context of a life cycle oriented approach
Jan-Iwo Jäkel, Robert Hartung, Katharina Klemt‐Albert
Computing in construction (2022)
Open Access | Times Cited: 6
Benchmarking Deep Learning models and hyperparameters for Bridge Defects Classification
Somayeh Shahrabadi, Dibet Gonzalez, Nuno Sousa, et al.
Procedia Computer Science (2023) Vol. 219, pp. 345-353
Open Access | Times Cited: 3
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