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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 Pipeline Leak Detection and Localization Approach Based on Ensemble TL1DCNN
Mengfei Zhou, Yanhui Yang, Yinze Xu, et al.
IEEE Access (2021) Vol. 9, pp. 47565-47578
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

The role of deep learning in urban water management: A critical review
Guangtao Fu, Yiwen Jin, Siao Sun, et al.
Water Research (2022) Vol. 223, pp. 118973-118973
Open Access | Times Cited: 202
Review on automated condition assessment of pipelines with machine learning
Yiming Liu, Yi Bao
Advanced Engineering Informatics (2022) Vol. 53, pp. 101687-101687
Closed Access | Times Cited: 103
Evaluation of deep learning approaches for oil & gas pipeline leak detection using wireless sensor networks
Christos Spandonidis, P. Theodoropoulos, Fotis Giannopoulos, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 113, pp. 104890-104890
Closed Access | Times Cited: 80
Pipeline leak diagnosis based on leak-augmented scalograms and deep learning
Muhammad Siddique, Zahoor Ahmad, Jong-Myon Kim
Engineering Applications of Computational Fluid Mechanics (2023) Vol. 17, Iss. 1
Open Access | Times Cited: 48
A Survey and Study of Signal and Data-Driven Approaches for Pipeline Leak Detection and Localization
Uma Rajasekaran, Mohanaprasad Kothandaraman
Journal of Pipeline Systems Engineering and Practice (2024) Vol. 15, Iss. 2
Closed Access | Times Cited: 15
A Method for Pipeline Leak Detection Based on Acoustic Imaging and Deep Learning
Sajjad Ahmad, Zahoor Ahmad, Cheol Hong Kim, et al.
Sensors (2022) Vol. 22, Iss. 4, pp. 1562-1562
Open Access | Times Cited: 48
Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review
Abdulnaser M. Al-Sabaeei, Hitham Alhussian, Said Jadid Abdulkadir, et al.
Energy Reports (2023) Vol. 10, pp. 1313-1338
Open Access | Times Cited: 31
Towards deep probabilistic graph neural network for natural gas leak detection and localization without labeled anomaly data
Xinqi Zhang, Jihao Shi, Xinyan Huang, et al.
Expert Systems with Applications (2023) Vol. 231, pp. 120542-120542
Open Access | Times Cited: 30
Pipeline Multipoint Leakage Detection Method Based on KKL-MSCNN
Xianming Lang, Li Yuan, Shuaiyong Li, et al.
IEEE Sensors Journal (2024) Vol. 24, Iss. 7, pp. 11438-11449
Closed Access | Times Cited: 12
Pipeline Leak Detection System for a Smart City: Leveraging Acoustic Emission Sensing and Sequential Deep Learning
N. Ullah, Muhammad Siddique, Saif Ullah, et al.
Smart Cities (2024) Vol. 7, Iss. 4, pp. 2318-2338
Open Access | Times Cited: 7
Safe and Secure Oil and Gas Pipeline Transportation System Based on Industrial Internet of Things
Ravi Sharma, Balázs Villányi
IEEE Sensors Journal (2024) Vol. 24, Iss. 5, pp. 6834-6845
Closed Access | Times Cited: 5
Application of machine learning to leakage detection of fluid pipelines in recent years: A review and prospect
Jianwu Chen, Xiao Wu, Zhibo Jiang, et al.
Measurement (2025), pp. 116857-116857
Closed Access
Fused deep neural networks for sustainable and computational management of heat-transfer pipeline diagnosis
Honggeun Ji, ChaeHee An, Minyoung Lee, et al.
Developments in the Built Environment (2023) Vol. 14, pp. 100144-100144
Open Access | Times Cited: 14
Machine Learning Model for Leak Detection Using Water Pipeline Vibration Sensor
Suan Lee, B. Kim
Sensors (2023) Vol. 23, Iss. 21, pp. 8935-8935
Open Access | Times Cited: 14
Underwater Gas Leak Quantification by Convolutional Neural Network Using Images
Gustavo Luís Rodrigues Caldas, Roger Matsumoto Moreira, Maurício B. de Souza
Processes (2025) Vol. 13, Iss. 1, pp. 118-118
Open Access
Deep Neural Network-Based Intelligent Health Monitoring System for Oil and Gas Pipelines
Mohamed Almahakeri, Ahmad Jobran Al-Mahasneh, Mohammed Abu Mallouh, et al.
Applied Soft Computing (2025) Vol. 171, pp. 112827-112827
Closed Access
P-DETR: A Transformer-Based Algorithm for Pipeline Structure Detection
Ibrahim Akinjobi Aromoye, Lo Hai Hiung, Patrick Sébastian
Results in Engineering (2025), pp. 104652-104652
Open Access
Digital twin for leak detection and fault diagnostics in gas pipelines: A systematic review, model development, and case study
Wahib A. Al‐Ammari, Ahmad K. Sleiti, Mohammad Azizur Rahman, et al.
Alexandria Engineering Journal (2025) Vol. 123, pp. 91-111
Closed Access
Developments of leak detection, diagnostics, and prediction algorithms in multiphase flows
Seshu Kumar Vandrangi, ‪Tamiru Alemu Lemma, Syed Muhammad Mujtaba, et al.
Chemical Engineering Science (2021) Vol. 248, pp. 117205-117205
Closed Access | Times Cited: 31
An intelligent water supply pipeline leakage detection method based on SV-WTBSVM
Xiaoting Guo, Huadong Song, Yanli Zeng, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 4, pp. 046125-046125
Closed Access | Times Cited: 3
Multisource Multimodal Feature Fusion for Small Leak Detection in Gas Pipelines
Wendi Yan, Wei Liu, Qiao Zhang, et al.
IEEE Sensors Journal (2023) Vol. 24, Iss. 2, pp. 1857-1865
Closed Access | Times Cited: 8
A Reliable Pipeline Leak Detection Method Using Acoustic Emission with Time Difference of Arrival and Kolmogorov–Smirnov Test
Duc-Thuan Nguyen, Tuan-Khai Nguyen, Zahoor Ahmad, et al.
Sensors (2023) Vol. 23, Iss. 23, pp. 9296-9296
Open Access | Times Cited: 7
Towards a more realistic approach to the problem of detecting fuel leaks in filling stations: Mixed time windows
Pedro Toledo, Rafael Arnay, Javier Hernández, et al.
Journal of Cleaner Production (2024) Vol. 468, pp. 143094-143094
Open Access | Times Cited: 2
Leak identification and quantification in gas network using operational data and deep learning framework
Elham Ebrahimi, Mohammadrahim Kazemzadeh, Antonio Ficarella
Sustainable Energy Grids and Networks (2024) Vol. 39, pp. 101496-101496
Open Access | Times Cited: 2
Gas pipeline safety management system based on neural network
Syed Muhammad Mujtaba, ‪Tamiru Alemu Lemma, Seshu Kumar Vandrangi
Process Safety Progress (2022) Vol. 41, Iss. S1
Closed Access | Times Cited: 10
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