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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:

Automated rail surface crack analytics using deep data-driven models and transfer learning
Zhong Zheng, Haoyang Qi, Zhuang Li, et al.
Sustainable Cities and Society (2021) Vol. 70, pp. 102898-102898
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Deep and transfer learning for building occupancy detection: A review and comparative analysis
Aya Nabil Sayed, Yassine Himeur, Fayçal Bensaali
Engineering Applications of Artificial Intelligence (2022) Vol. 115, pp. 105254-105254
Open Access | Times Cited: 88
Next-generation energy systems for sustainable smart cities: Roles of transfer learning
Yassine Himeur, Mariam Elnour, Fodil Fadli, et al.
Sustainable Cities and Society (2022) Vol. 85, pp. 104059-104059
Open Access | Times Cited: 87
Deep learning for surface crack detection in civil engineering: A comprehensive review
Haiyan Zhuang, Yikai Cheng, Man Zhou, et al.
Measurement (2025), pp. 116908-116908
Closed Access | Times Cited: 2
CNN Based on Transfer Learning Models Using Data Augmentation and Transformation for Detection of Concrete Crack
Md. Monirul Islam, Md. Belal Hossain, Md. Nasim Akhtar, et al.
Algorithms (2022) Vol. 15, Iss. 8, pp. 287-287
Open Access | Times Cited: 67
A novel image-based transfer learning framework for cross-domain HVAC fault diagnosis: From multi-source data integration to knowledge sharing strategies
Cheng Fan, Weilin He, Yichen Liu, et al.
Energy and Buildings (2022) Vol. 262, pp. 111995-111995
Closed Access | Times Cited: 59
Wheat Ear Recognition Based on RetinaNet and Transfer Learning
Jingbo Li, Changchun Li, Shuaipeng Fei, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4845-4845
Open Access | Times Cited: 56
Defect classification based on deep features for railway tracks in sustainable transportation
İlhan Aydın, Erhan Akın, Mehmet Karaköse
Applied Soft Computing (2021) Vol. 111, pp. 107706-107706
Closed Access | Times Cited: 52
Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review
Camilo Laiton-Bonadiez, John W. Branch, Julián Andrés Zapata-Cortés, et al.
Sensors (2022) Vol. 22, Iss. 7, pp. 2491-2491
Open Access | Times Cited: 30
Deep Learning for Optical Sensor Applications: A Review
Nagi H. Al‐Ashwal, Khaled A. M. Al Soufy, Mohga E. Hamza, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6486-6486
Open Access | Times Cited: 18
MtlrNet: An Effective Deep Multitask Learning Architecture for Rail Crack Detection
Shijin Meng, Senyun Kuang, Zheng Ma, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-10
Closed Access | Times Cited: 23
Cross-dataset semantic segmentation for composite crack detection using unsupervised transfer learning
Pengchao Zhao, Wenyuan Xu, dequan qi, et al.
Composite Structures (2025), pp. 119071-119071
Closed Access
MSRConvNet: Classification of railway track defects using multi-scale residual convolutional neural network
Hakan Açıkgöz, Deniz Korkmaz
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 105965-105965
Closed Access | Times Cited: 11
Damage identification for railway tracks using ultrasound guided wave and hybrid probabilistic deep learning
Yang Zhang, Da-Zhi Dang, You‐Wu Wang, et al.
Construction and Building Materials (2024) Vol. 418, pp. 135466-135466
Closed Access | Times Cited: 4
Task similarity guided transfer learning for acoustic emission-based rail crack assessment
Si‐Xin Chen, Lu Zhou, Yi‐Qing Ni, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112404-112404
Closed Access
A pencil lead break-triggered, adversarial autoencoder-based approach for rapid and robust rail damage detection
Da-Zhi Dang, Boyang Su, You‐Wu Wang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 150, pp. 110637-110637
Closed Access
Vibration-based structural damage detection using 1-D convolutional neural network and transfer learning
Shuai Teng, Gongfa Chen, Zhaocheng Yan, et al.
Structural Health Monitoring (2022) Vol. 22, Iss. 4, pp. 2888-2909
Closed Access | Times Cited: 17
Semi-Supervised Deep Learning in High-Speed Railway Track Detection Based on Distributed Fiber Acoustic Sensing
Shulun Wang, Feng Liu, Bin Liu
Sensors (2022) Vol. 22, Iss. 2, pp. 413-413
Open Access | Times Cited: 16
Autonomous Rail Surface Defect Identification Based on an Improved One-Stage Object Detection Algorithm
Mengyi Wang, Yu Zhou
Journal of Performance of Constructed Facilities (2024) Vol. 38, Iss. 5
Closed Access | Times Cited: 3
Vision Image Monitoring on Transportation Infrastructures: A Lightweight Transfer Learning Approach
Yue Hou, Hongyu Shi, Ning Chen, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 24, Iss. 11, pp. 12888-12899
Closed Access | Times Cited: 15
An efficient approach for guided wave structural monitoring of switch rails via deep convolutional neural network-based transfer learning
Weixu Liu, Zhifeng Tang, Fuzai Lv, et al.
Measurement Science and Technology (2022) Vol. 34, Iss. 2, pp. 024004-024004
Closed Access | Times Cited: 14
Improved YOLOv5 Based on Feature Fusion and Attention Mechanism and Its Application in Continuous Casting Slab Detection
Hongliang Yang, Yiming Fang, Le Liu, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-16
Closed Access | Times Cited: 7
A fast and multifactor evacuation method considering cumulative fatality rate based on deep reinforcement learning for urban toxic gas leakage
Xuqiang Shao, Haokang Yang, Zhijian Liu, et al.
Sustainable Cities and Society (2024) Vol. 103, pp. 105255-105255
Closed Access | Times Cited: 2
Deep Learning for Optical Sensor Applications: An Insight Review
Nagi H. Al‐Ashwal, Khaled A. M. Al Soufy, Mohga E. Hamza, et al.
(2023)
Open Access | Times Cited: 5
A Review on Deep Learning Techniques for Railway Infrastructure Monitoring
M. Di Summa, Maria Elena Griseta, Nicola Mosca, et al.
IEEE Access (2023) Vol. 11, pp. 114638-114661
Open Access | Times Cited: 5
Utilizing Deep Learning for Defect Inspection in Hand Tool Assembly
Hong-Dar Lin, Cheng-Kai Jheng, Chou-Hsien Lin, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3635-3635
Open Access | Times Cited: 1
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