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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:

Deep Domain Adaptation for Pavement Crack Detection
Huijun Liu, Yang Chun-hua, Ao Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2022), pp. 1-13
Closed Access | Times Cited: 19

Showing 19 citing articles:

From global challenges to local solutions: A review of cross-country collaborations and winning strategies in road damage detection
Deeksha Arya, Hiroya Maeda, Yoshihide Sekimoto
Advanced Engineering Informatics (2024) Vol. 60, pp. 102388-102388
Closed Access | Times Cited: 15
Self‐training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation
Pang-jo CHUN, T. Kikuta
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 17, pp. 2642-2661
Open Access | Times Cited: 13
Visual Concrete Bridge Defect Classification and Detection Using Deep Learning: A Systematic Review
Dariush Amirkhani, Mohand Saïd Allili, Loucif Hebbache, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 9, pp. 10483-10505
Closed Access | Times Cited: 10
Preserving Label-Related Domain-Specific Information for Cross-Domain Semantic Segmentation
Muxin Liao, Shishun Tian, Yuhang Zhang, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 10, pp. 14917-14931
Closed Access | Times Cited: 5
A three-stage pavement image crack detection framework with positive sample augmentation
Qingsong Song, Li Liu, Na Lü, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 129, pp. 107624-107624
Closed Access | Times Cited: 12
Unsupervised domain adaptation-based crack segmentation using transformer network
Daniel Asefa Beyene, Dai Quoc Tran, Michael Bekele Maru, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 107889-107889
Closed Access | Times Cited: 11
TransMF: Transformer-Based Multi-Scale Fusion Model for Crack Detection
Xiaochen Ju, Xinxin Zhao, Shengsheng Qian
Mathematics (2022) Vol. 10, Iss. 13, pp. 2354-2354
Open Access | Times Cited: 14
Self-Supervised Adversarial Learning for Domain Adaptation of Pavement Distress Classification
Yanwen Wu, Mingjian Hong, Ao Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2023) Vol. 25, Iss. 2, pp. 1966-1977
Closed Access | Times Cited: 6
Domain adversarial training for classification of cracking in images of concrete surfaces
Bruno Oliveira Santos, Jónatas Valença, João Paulo Costeira, et al.
AI in Civil Engineering (2022) Vol. 1, Iss. 1
Open Access | Times Cited: 8
RCD-IIUM: A Comprehensive Malaysian Road Crack Dataset for Infrastructure Analysis
Arselan Ashraf, Ali Sophian, Amir Akramin Shafie, et al.
(2024) Vol. 2, pp. 200-206
Closed Access | Times Cited: 1
Multi-source Domain Adaptation for Unsupervised Road Defect Segmentation
Jongmin Yu, Hyeontaek Oh, Sebastiano Fichera, et al.
(2023)
Closed Access | Times Cited: 3
Image-to-Image Translation-Based Structural Damage Data Augmentation for Infrastructure Inspection Using Unmanned Aerial Vehicle
Gi-Hun Gwon, Jin-Hwan Lee, In‐Ho Kim, et al.
Drones (2023) Vol. 7, Iss. 11, pp. 666-666
Open Access | Times Cited: 2
Pavement Disease Detection Network Based on Enhanced Spatial Attention and Dc2f
Siyuan Lin, Yiquan Wu
(2024)
Closed Access
StreetLens
Amani Abu Jabal, Abdullah Alfarrarjeh, Suhib Alsaggar, et al.
(2024), pp. 415-421
Closed Access
Recent advances in crack detection technologies for structures: a survey of 2022-2023 literature
Hessam Kaveh, Reda Alhajj
Frontiers in Built Environment (2024) Vol. 10
Open Access
Research on Methods of Pavement Distress Detection Based on Object Detection Convolutional Neural Network
Xingang Wang, Yaxin Huang, Yongjun Shao, et al.
(2024), pp. 390-394
Closed Access
Mixed Reality-Based Concrete Crack Detection and Skeleton Extraction Using Deep Learning and Image Processing
Davood Shojaei, Peyman Jafary, Zezheng Zhang
Electronics (2024) Vol. 13, Iss. 22, pp. 4426-4426
Open Access
Crack Detection, Classification, and Segmentation on Road Pavement Material Using Multi-Scale Feature Aggregation and Transformer-Based Attention Mechanisms
Arselan Ashraf, Ali Sophian, Ali Aryo Bawono
Construction Materials (2024) Vol. 4, Iss. 4, pp. 655-675
Open Access
Domain adaptation and knowledge distillation for lightweight pavement crack detection
T.S. Xiao, Rong Pang, Huijun Liu, et al.
Expert Systems with Applications (2024) Vol. 263, pp. 125734-125734
Closed Access
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