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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:

A Novel Approach to Automated 3D Spalling Defects Inspection in Railway Tunnel Linings Using Laser Intensity and Depth Information
Mingliang Zhou, Wen Cheng, Hongwei Huang, et al.
Sensors (2021) Vol. 21, Iss. 17, pp. 5725-5725
Open Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

A deep learning-based approach for refined crack evaluation from shield tunnel lining images
Shuai Zhao, Dongming Zhang, Yadong Xue, et al.
Automation in Construction (2021) Vol. 132, pp. 103934-103934
Closed Access | Times Cited: 85
Digital technology for quality management in construction: A review and future research directions
Hanbin Luo, Ling Lin, Ke Chen, et al.
Developments in the Built Environment (2022) Vol. 12, pp. 100087-100087
Open Access | Times Cited: 55
Seg2Tunnel: A hierarchical point cloud dataset and benchmarks for segmentation of segmental tunnel linings
Wei Lin, Brian Sheil, Pin Zhang, et al.
Tunnelling and Underground Space Technology (2024) Vol. 147, pp. 105735-105735
Closed Access | Times Cited: 12
SAM4Tun: No-training model for tunnel lining point cloud component segmentation
Zehao Ye, Wei Lin, Asaad Faramarzi, et al.
Tunnelling and Underground Space Technology (2025) Vol. 158, pp. 106401-106401
Open Access | Times Cited: 1
Transforming the maintenance of underground infrastructure through Digital Twins: State of the art and outlook
Huamei Zhu, Mengqi Huang, Pei-Qi Ji, et al.
Tunnelling and Underground Space Technology (2025) Vol. 161, pp. 106508-106508
Open Access | Times Cited: 1
3D spatial measurement for model reconstruction: A review
Wendy Flores-Fuentes, Gabriel Trujillo-Hernández, Ivan Yeniseysk Alba-Corpus, et al.
Measurement (2022) Vol. 207, pp. 112321-112321
Closed Access | Times Cited: 36
STSD:A large-scale benchmark for semantic segmentation of subway tunnel point cloud
Hao Cui, Jian Li, Qingzhou Mao, et al.
Tunnelling and Underground Space Technology (2024) Vol. 150, pp. 105829-105829
Closed Access | Times Cited: 7
Effect of different imaging modalities on the performance of a CNN: An experimental study on damage segmentation in infrared, visible, and fused images of concrete structures
Sandra Pozzer, Marcos Paulo Vieira de Souza, Bata Hena, et al.
NDT & E International (2022) Vol. 132, pp. 102709-102709
Closed Access | Times Cited: 25
Concrete spalling detection system based on semantic segmentation using deep architectures
Tamanna Yasmin, Duc La, Kien T. La, et al.
Computers & Structures (2024) Vol. 300, pp. 107398-107398
Closed Access | Times Cited: 6
Rail transit shield tunnel deformation detection method based on cloth simulation filtering with point cloud cylindrical projection
Bo Shi, Mi Yang, Jian Liu, et al.
Tunnelling and Underground Space Technology (2023) Vol. 135, pp. 105031-105031
Closed Access | Times Cited: 12
Shield Tunnel Dislocation Detection Method Based on Semantic Segmentation and Bolt Hole Positioning of MLS Point Cloud
Hao Cui, Qingzhou Mao, Jian Li, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-15
Closed Access | Times Cited: 4
Improved Quantitative Analysis of Concrete Defect Volumes Using Enhanced Point Cloud Slicing Methodology
Peng Xu, Yonglong Li, Fuqiang Gou, et al.
IEEE Transactions on Instrumentation and Measurement (2025) Vol. 74, pp. 1-18
Closed Access
Structural geometry-informed 3D deep learning for segmental tunnel lining analysis in point clouds
Wei Lin, Brian Sheil, Pin Zhang, et al.
Automation in Construction (2025) Vol. 176, pp. 106281-106281
Closed Access
A Novel Detection and Assessment Method for Operational Defects of Pipe Jacking Tunnel Based on 3D Longitudinal Deformation Curve: A Case Study
Wei Lin, Pan Li, Xiongyao Xie
Sensors (2022) Vol. 22, Iss. 19, pp. 7648-7648
Open Access | Times Cited: 16
Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels
Ziren Yin, Zhanzhan Lei, Ao Zheng, et al.
Sensors (2023) Vol. 23, Iss. 16, pp. 7106-7106
Open Access | Times Cited: 9
Assessment of out‐of‐plane structural defects using parallel laser line scanning system
Chaobin Li, R.K.L. Su, Xiao Pan
Computer-Aided Civil and Infrastructure Engineering (2023) Vol. 39, Iss. 6, pp. 834-851
Open Access | Times Cited: 9
A Systematic Review of Automated Construction Inspection and Progress Monitoring (ACIPM): Applications, Challenges, and Future Directions
Reihaneh Samsami
CivilEng (2024) Vol. 5, Iss. 1, pp. 265-287
Open Access | Times Cited: 3
Automated masonry spalling severity segmentation in historic railway tunnels using deep learning and a block face plane fitting approach
J. Carson Smith, Chrysothemis Paraskevopoulou, Anthony G. Cohn, et al.
Tunnelling and Underground Space Technology (2024) Vol. 153, pp. 106043-106043
Open Access | Times Cited: 3
Automated 3D defect inspection in shield tunnel linings through integration of image and point cloud data
Hongwei Huang, Shuyi Liu, Mingliang Zhou, et al.
AI in Civil Engineering (2025) Vol. 4, Iss. 1
Open Access
A hierarchical DCNN-based approach for classifying imbalanced water inflow in rock tunnel faces
Jiayao Chen, Hongwei Huang, Anthony G. Cohn, et al.
Tunnelling and Underground Space Technology (2022) Vol. 122, pp. 104399-104399
Open Access | Times Cited: 13
Intelligent monitoring and residual analysis of tunnel point cloud data based on free-form approximation
Xiangyang Xu, Zihan Wang, Peixin Shi, et al.
Mechanics of Advanced Materials and Structures (2022) Vol. 30, Iss. 8, pp. 1703-1712
Closed Access | Times Cited: 13
3D Deep Learning for Segmentation of Masonry Tunnel Joints
J. C. Smith, Chrysothemis Paraskevopoulou
Procedia Structural Integrity (2024) Vol. 64, pp. 220-227
Open Access | Times Cited: 2
Hammering sound of concrete with defects and spalling risk
Naotoshi Yasuda
Tunnelling and Underground Space Technology (2022) Vol. 131, pp. 104789-104789
Closed Access | Times Cited: 10
Theoretical, Numerical, and Experimental Study on the Identification of Subway Tunnel Structural Damage Based on the Moving Train Dynamic Response
Hongqiao Li, Xiongyao Xie, Yonglai Zhang, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7197-7197
Open Access | Times Cited: 12
Deep learning for masonry lined tunnel condition assessment
J. C. Smith, Chrysothemis Paraskevopoulou, A. Bedi, et al.
CRC Press eBooks (2023), pp. 2910-2917
Open Access | Times Cited: 5
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