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 Pipeline Corrosion Monitoring Method Based on Piezoelectric Active Sensing and CNN
Dan Yang, Xinyi Zhang, Ti Zhou, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 855-855
Open Access | Times Cited: 9
Dan Yang, Xinyi Zhang, Ti Zhou, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 855-855
Open Access | Times Cited: 9
Showing 9 citing articles:
A Novel Pipeline Age Evaluation: Considering Overall Condition Index and Neural Network Based on Measured Data
Hassan Noroznia, Majid Gandomkar, Javad Nikoukar, et al.
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 1, pp. 252-268
Open Access | Times Cited: 16
Hassan Noroznia, Majid Gandomkar, Javad Nikoukar, et al.
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 1, pp. 252-268
Open Access | Times Cited: 16
An Adaptive Grid Generation Approach to Pipeline Leakage Rapid Localization Based on Time Reversal
Yu Wang, Haoyang Chen, Yang Yang, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1753-1753
Open Access
Yu Wang, Haoyang Chen, Yang Yang, et al.
Sensors (2025) Vol. 25, Iss. 6, pp. 1753-1753
Open Access
Advanced Machine Learning Techniques for Corrosion Rate Estimation and Prediction in Industrial Cooling Water Pipelines
Desireé Ruiz, Abraham Casas, C. Escobar, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3564-3564
Open Access | Times Cited: 4
Desireé Ruiz, Abraham Casas, C. Escobar, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3564-3564
Open Access | Times Cited: 4
A pipeline corrosion detecting method using percussion and residual neural network
Dan Yang, Songlin Ji, Tao Wang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086009-086009
Closed Access | Times Cited: 2
Dan Yang, Songlin Ji, Tao Wang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086009-086009
Closed Access | Times Cited: 2
A critical analysis of machine learning in ship, offshore, and oil & gas corrosion research, part I: Corrosion detection and classification
Muhammad Imran, Mohammad Ilyas Khan, Shahrizan Jamaludin, et al.
Ocean Engineering (2024) Vol. 313, pp. 119600-119600
Closed Access | Times Cited: 2
Muhammad Imran, Mohammad Ilyas Khan, Shahrizan Jamaludin, et al.
Ocean Engineering (2024) Vol. 313, pp. 119600-119600
Closed Access | Times Cited: 2
Piezoelectric Active Sensing-Based Pipeline Corrosion Monitoring Using Singular Spectrum Analysis
Dan Yang, Wang Hu, Tao Wang, et al.
Sensors (2024) Vol. 24, Iss. 13, pp. 4192-4192
Open Access | Times Cited: 1
Dan Yang, Wang Hu, Tao Wang, et al.
Sensors (2024) Vol. 24, Iss. 13, pp. 4192-4192
Open Access | Times Cited: 1
A Review of Deformations Prediction for Oil and Gas Pipelines Using Machine and Deep Learning
Bruno Macedo, Tales Humberto de Aquino Boratto, Camila Martins Saporetti, et al.
Studies in systems, decision and control (2024), pp. 289-317
Closed Access
Bruno Macedo, Tales Humberto de Aquino Boratto, Camila Martins Saporetti, et al.
Studies in systems, decision and control (2024), pp. 289-317
Closed Access
Deep learning enabled in vitro predicting biological tissue thickness using force measurement device
Haibin Hu, Sheng Tan, Jie Hu
Computers in Biology and Medicine (2024) Vol. 182, pp. 109181-109181
Closed Access
Haibin Hu, Sheng Tan, Jie Hu
Computers in Biology and Medicine (2024) Vol. 182, pp. 109181-109181
Closed Access
Video Analytics using Deep Learning in Cloud Services to Detect Corrosion - A Comprehensive Survey
S Suresh Kumar, K Gokul, I Hemanand, et al.
(2023), pp. 949-955
Closed Access
S Suresh Kumar, K Gokul, I Hemanand, et al.
(2023), pp. 949-955
Closed Access
