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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:

Segment-based pavement crack quantification
Xingxing Weng, Yuchun Huang, Wenzong Wang
Automation in Construction (2019) Vol. 105, pp. 102819-102819
Closed Access | Times Cited: 63

Showing 26-50 of 63 citing articles:

Semi-automatic crack width measurement using an OrthoBoundary algorithm
Zhe Li, Yi Miao, Mehran Eskandari Torbaghan, et al.
Automation in Construction (2023) Vol. 158, pp. 105251-105251
Closed Access | Times Cited: 9
Promoting Automatic Detection of Road Damage: A High-Resolution Dataset, a New Approach, and a New Evaluation Criterion
Tianxiang Yin, Wei Zhang, Jinqiao Kou, et al.
IEEE Transactions on Automation Science and Engineering (2024) Vol. 22, pp. 2472-2484
Closed Access | Times Cited: 3
DCUFormer: Enhancing pavement crack segmentation in complex environments with dual-cross/upsampling attention
Jinhuan Shan, Yue Huang, Wei Jiang
Expert Systems with Applications (2024), pp. 125891-125891
Closed Access | Times Cited: 3
CCapFPN: A Context-Augmented Capsule Feature Pyramid Network for Pavement Crack Detection
Yongtao Yu, Haiyan Guan, Dilong Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2020) Vol. 23, Iss. 4, pp. 3324-3335
Closed Access | Times Cited: 27
An improved minimal path selection approach with new strategies for pavement crack segmentation
Yizheng Chen, Liang Jia, Xingyu Gu, et al.
Measurement (2021) Vol. 184, pp. 109877-109877
Closed Access | Times Cited: 20
A Deep-Convolutional-Neural-Network-Based Semi-Supervised Learning Method for Anomaly Crack Detection
Xingjun Gao, Chuansheng Huang, Shuai Teng, et al.
Applied Sciences (2022) Vol. 12, Iss. 18, pp. 9244-9244
Open Access | Times Cited: 14
Integration of Smart Pavement Data with Decision Support Systems: A Systematic Review
Margarida Amândio, Manuel Parente, José Neves, et al.
Buildings (2021) Vol. 11, Iss. 12, pp. 579-579
Open Access | Times Cited: 18
EAFNet: Extraction-amplification-fusion network for tiny cracks detection
Z. Zhou, Wensong Zhao, Kechen Song, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 134, pp. 108691-108691
Closed Access | Times Cited: 2
Unsupervised defect detection with patch-aware mutual reasoning network in image data
Yanyan Wang, Kechen Song, Menghui Niu, et al.
Automation in Construction (2022) Vol. 142, pp. 104472-104472
Closed Access | Times Cited: 12
Curve‐based crack detection using crack information gain
Qi Chen, Yuchun Huang, Xingxing Weng, et al.
Structural Control and Health Monitoring (2021) Vol. 28, Iss. 8
Open Access | Times Cited: 15
Automated Pixel-Level Deep Crack Segmentation on Historical Surfaces Using U-Net Models
Esraa Elhariri, Nashwa El-Bendary, Shereen A. Taie
Algorithms (2022) Vol. 15, Iss. 8, pp. 281-281
Open Access | Times Cited: 9
Research on Real-Time Detection Algorithm for Pavement Cracks Based on SparseInst-CDSM
Shaojie Wang, Jikai Zhang, Xiaoqi Lu
Mathematics (2023) Vol. 11, Iss. 15, pp. 3277-3277
Open Access | Times Cited: 4
Extraction and measurement of recessive and conventional cracks in underground engineering concrete structures
Wenchong Tang, Liang Tang, Xiangxun Kong, et al.
Journal of Building Engineering (2024) Vol. 94, pp. 110010-110010
Closed Access | Times Cited: 1
Automated quantification of crack length and width in asphalt pavements
Zhe Li, Tuo Zhang, Yi Miao, et al.
Computer-Aided Civil and Infrastructure Engineering (2024)
Open Access | Times Cited: 1
Enhancing automated health monitoring of road infrastructure through a hierarchical robust deep learning approach
Fuwen Deng, Jiandong Jin, Xiaobo Chen, et al.
Structural Health Monitoring (2024)
Closed Access | Times Cited: 1
Survey of automated crack detection methods for asphalt and concrete structures
Oumaima Khlifati, Khadija Baba, Bassam A. Tayeh
Innovative Infrastructure Solutions (2024) Vol. 9, Iss. 11
Closed Access | Times Cited: 1
Exposed Aggregate Detection of Stilling Basin Slabs Using Attention U-Net Network
Yonglong Li, Xiaoxia Li, Haoran Wang, et al.
KSCE Journal of Civil Engineering (2020) Vol. 24, Iss. 6, pp. 1740-1749
Closed Access | Times Cited: 10
Segmentation Method for Enhancing the Continuity and Integrality of Microcracks in Concrete Fracture XCT Image
Shuxian Hong, Chuan Kuang, Jianchao Zhang, et al.
Journal of Materials in Civil Engineering (2021) Vol. 34, Iss. 3
Closed Access | Times Cited: 9
State of the Art and a New Methodology Based on Multi-agent Fuzzy System for Concrete Crack Detection and Type Classification
Mahsa Payab, Mostafa Khanzadi
Archives of Computational Methods in Engineering (2020) Vol. 28, Iss. 4, pp. 2509-2542
Closed Access | Times Cited: 7
Image-processing-based automatic crack detection and classification for refractory evaluation
Guanzheng Wang, Fangguan Tan, Shengli Jin, et al.
Ceramics International (2022) Vol. 48, Iss. 16, pp. 23232-23240
Closed Access | Times Cited: 4
Optimization Model for the Pavement Pothole Repair Problem Considering Consumable Resources
Shu‐Shun Liu, Agung Budiwirawan, Muhammad Faizal Ardhiansyah Arifin, et al.
Symmetry (2021) Vol. 13, Iss. 3, pp. 364-364
Open Access | Times Cited: 5
Implementation of the Drones with Deep-Learning Crack Detection Analysis for Inspection of Bridge
Seung Hyun Paik, Dae-Young Choi, Young-Kyu Kim, et al.
The Journal of Korean Institute of Information Technology (2021) Vol. 19, Iss. 3, pp. 45-52
Closed Access | Times Cited: 4
Deep-Learning Crack Analysis for Visual-Safety Inspection of Bridge by Drones
Daeyoung Choi, Seung Hyun Paik, Young-Kyu Kim, et al.
The Journal of Korean Institute of Information Technology (2021) Vol. 19, Iss. 12, pp. 115-121
Closed Access | Times Cited: 4
Crack-SAM: Crack Segmentation Using a Foundation Model
R Rakshitha, S Srinath, N. Vinay Kumar, et al.
Research Square (Research Square) (2024)
Open Access
Crack SAM: enhancing crack detection utilizing foundation models and Detectron2 architecture
R. Rakshitha, S Srinath, N. Vinay Kumar, et al.
Journal of Infrastructure Preservation and Resilience (2024) Vol. 5, Iss. 1
Open Access

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