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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:

Workmanship defect classification in medium voltage cable terminations with convolutional neural network
Halil Ibrahim Uckol, Suat İlhan, Aydoğan Özdemir
Electric Power Systems Research (2021) Vol. 194, pp. 107105-107105
Closed Access | Times Cited: 21

Showing 21 citing articles:

Hypertuned-YOLO for interpretable distribution power grid fault location based on EigenCAM
Stéfano Frizzo Stefenon, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, et al.
Ain Shams Engineering Journal (2024) Vol. 15, Iss. 6, pp. 102722-102722
Open Access | Times Cited: 13
A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques
Haresh Kumar, Muhammad Shafiq, Kimmo Kauhaniemi, et al.
Energies (2024) Vol. 17, Iss. 5, pp. 1142-1142
Open Access | Times Cited: 12
Convolutional Neural Network-Based Pattern Recognition of Partial Discharge in High-Speed Electric-Multiple-Unit Cable Termination
Chuanming Sun, Guangning Wu, Guixiang Pan, et al.
Sensors (2024) Vol. 24, Iss. 8, pp. 2660-2660
Open Access | Times Cited: 7
Investigation of electrical tree growth characteristics and partial discharge pattern analysis using deep neural network
Rakesh Sahoo, Subrata Karmakar
Electric Power Systems Research (2023) Vol. 220, pp. 109287-109287
Closed Access | Times Cited: 18
Deep Learning in High Voltage Engineering: A Literature Review
Sara Mantach, Abdulla Lutfi, Hamed Moradi Tavasani, et al.
Energies (2022) Vol. 15, Iss. 14, pp. 5005-5005
Open Access | Times Cited: 27
XLPE cable joint defects measurement method based on point cloud remapping
Lei Deng, Hao Deng, Guihua Liu, et al.
Measurement (2024) Vol. 226, pp. 114139-114139
Closed Access | Times Cited: 4
An efficient accuracy improvement method for cable defect location based on instantaneous filtering in time-frequency domain
Xingyu Zou, Haibao Mu, Renjie Wang, et al.
Measurement (2024) Vol. 226, pp. 114178-114178
Closed Access | Times Cited: 4
A cable insulation defect classification method based on CNN-transformer
Ning Zhao, Zhiguo Duan, Qian Li, et al.
Frontiers in Physics (2024) Vol. 12
Open Access | Times Cited: 3
Identification of corona discharges based on wavelet scalogram images with deep convolutional neural networks
Halil Ibrahim Uckol, Suat İlhan
Electric Power Systems Research (2023) Vol. 224, pp. 109712-109712
Closed Access | Times Cited: 10
Characterization of DC corona discharge current pulses using high-frequency measurement techniques
Halil Ibrahim Uckol, Suat İlhan
Measurement (2023) Vol. 218, pp. 113154-113154
Closed Access | Times Cited: 9
Investigations of Corona Discharge Images for Rod-Rod Electrode System Under HVDC
Halil Ibrahim Uckol, Idris Ozdemir, Suat İlhan
2022 57th International Universities Power Engineering Conference (UPEC) (2023), pp. 1-4
Closed Access | Times Cited: 3
Harmonic-based 3D thermal analysis of thyristor-controlled reactor's power cable joints considering external electromagnetic fields
Ahmadreza Jamali-Abnavi, Hamed Hashemi‐Dezaki
Electric Power Systems Research (2021) Vol. 205, pp. 107727-107727
Closed Access | Times Cited: 7
Novel data augmentation for improved insulation fault diagnosis under nonideal condition
Wong Jee Keen Raymond, Hazlee Azil Illias, Hazlie Mokhlis
Expert Systems with Applications (2022) Vol. 209, pp. 118390-118390
Closed Access | Times Cited: 5
Comparative Investigation of Corona Pulse Characteristics under DC and AC Voltages
Halil Ibrahim Uckol, Taylan Ozgur Bilgic, Suat İlhan
2022 IEEE International Conference on High Voltage Engineering and Applications (ICHVE) (2022), pp. 1-4
Closed Access | Times Cited: 4
Enhanced Fault Type Detection in Covered Conductors Using a Stacked Ensemble and Novel Algorithm Combination
Ondřej Kabot, Lukáš Klein, Lukáš Prokop, et al.
Sensors (2023) Vol. 23, Iss. 20, pp. 8353-8353
Open Access | Times Cited: 2
Bayesian Optimized Convolution Neural Network Architecture for Partial Discharge Signature Recognition
P. Ramkumar, Nupur Prakash, B. Vigneshwaran
(2024), pp. 415-420
Closed Access
A partial discharge pattern recognition method based on multi-scale adaptive denoising network and Stacking Ensemble Learning
Shangpo Zheng, Junfeng Liu, Jun Zeng
Electric Power Systems Research (2024) Vol. 241, pp. 111392-111392
Closed Access
Detection and Classification of Partial Discharge by Hybrid Neural Network Algorithms in Air-insulated MV Switchgear
Paweł Kluge, A. Łasica, Jacek Starzyński
(2023)
Open Access | Times Cited: 1
Analytical investigations on discrimination of partial discharge defective cable termination among healthy ones with joint sheath‐ground connection
Abbas Babaee, Kian Shahinfar, S. Mohammad Shahrtash
IET Generation Transmission & Distribution (2022) Vol. 16, Iss. 16, pp. 3197-3207
Open Access | Times Cited: 1
Optical Methods for Detecting Local Microdefects in Cable Products
Ivan Razuvaev, Evgeny Fedorov, Vitaly Redko
Engineering materials (2023), pp. 51-59
Closed Access
Recognition of Partial Discharge Signatures using Convolution Neural Network
R. Naga Sai Harshini, S.R. Vishnu Rajeesh, M.D. Kiruthikathangarathi, et al.
(2022), pp. 182-186
Closed Access
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