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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:

An unsupervised bearing fault diagnosis based on deep subdomain adaptation under noise and variable load condition
Mohammadreza Ghorvei, Mohammadreza Kavianpour, Mohammad Taghi Hamidi Beheshti, et al.
Measurement Science and Technology (2021) Vol. 33, Iss. 2, pp. 025901-025901
Closed Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Spatial graph convolutional neural network via structured subdomain adaptation and domain adversarial learning for bearing fault diagnosis
Mohammadreza Ghorvei, Mohammadreza Kavianpour, Mohammad Taghi Hamidi Beheshti, et al.
Neurocomputing (2022) Vol. 517, pp. 44-61
Open Access | Times Cited: 77
A CNN-BiLSTM model with attention mechanism for earthquake prediction
Parisa Kavianpour, Mohammadreza Kavianpour, Ehsan Jahani, et al.
The Journal of Supercomputing (2023) Vol. 79, Iss. 17, pp. 19194-19226
Open Access | Times Cited: 62
Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation
Bin Yang, Yaguo Lei, Xiang Li, et al.
IEEE/CAA Journal of Automatica Sinica (2024) Vol. 11, Iss. 4, pp. 932-945
Closed Access | Times Cited: 22
Modified DSAN for unsupervised cross-domain fault diagnosis of bearing under speed fluctuation
Jingjie Luo, Haidong Shao, Hongru Cao, et al.
Journal of Manufacturing Systems (2022) Vol. 65, pp. 180-191
Open Access | Times Cited: 45
A New Adversarial Domain Generalization Network Based on Class Boundary Feature Detection for Bearing Fault Diagnosis
Jingde Li, Changqing Shen, Lin Kong, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-9
Open Access | Times Cited: 42
A class alignment method based on graph convolution neural network for bearing fault diagnosis in presence of missing data and changing working conditions
Mohammadreza Kavianpour, Amin Ramezani, Mohammad Taghi Hamidi Beheshti
Measurement (2022) Vol. 199, pp. 111536-111536
Closed Access | Times Cited: 41
A novel generalized source-free domain adaptation approach for cross-domain industrial fault diagnosis
Jilun Tian, Jiusi Zhang, Yuchen Jiang, et al.
Reliability Engineering & System Safety (2023) Vol. 243, pp. 109891-109891
Closed Access | Times Cited: 30
On the effects of data normalization for domain adaptation on EEG data
Andrea Apicella, Francesco Isgrò, Andrea Pollastro, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106205-106205
Open Access | Times Cited: 25
A deep targeted transfer network with clustering pseudo-label learning for fault diagnosis across different Machines
Feiyu Lu, Qingbin Tong, Xuedong Jiang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 213, pp. 111344-111344
Closed Access | Times Cited: 12
Self-supervised feature extraction via time–frequency contrast for intelligent fault diagnosis of rotating machinery
Yang Liu, Weigang Wen, Yihao Bai, et al.
Measurement (2023) Vol. 210, pp. 112551-112551
Closed Access | Times Cited: 14
A universal fault diagnosis framework for marine machinery based on domain adaptation
Yu Guo, Jundong Zhang, Bin Sun, et al.
Ocean Engineering (2024) Vol. 302, pp. 117729-117729
Closed Access | Times Cited: 5
Domain-alignment multitask learning network for partial discharge condition assessment with digital twin in gas-insulated switchgear
Jing Yan, Yanxin Wang, Wenjie Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 065109-065109
Closed Access | Times Cited: 4
Damage identification of truss bridges based on feature transferable digital twins
Zhou Huang, Xinfeng Yin, Yang Liu, et al.
Measurement (2024) Vol. 233, pp. 114735-114735
Closed Access | Times Cited: 4
A new cross-domain approach for bearing fault diagnosis based on multiscale convolutional networks and adversarial subdomain adaptation
Haibin Sun, Weilong Zhu
Nondestructive Testing And Evaluation (2025), pp. 1-29
Closed Access
Unsupervised rolling bearing fault diagnosis method across working conditions based on multiscale convolutional neural network
H.C. Fu, Di Yu, Changshu Zhan, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 3, pp. 035018-035018
Closed Access | Times Cited: 10
Novel imbalanced subdomain adaption multiscale convolutional network for cross-domain unsupervised fault diagnosis of rolling bearings
Tianlong Huo, Linfeng Deng, Bo Zhang, et al.
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015905-015905
Closed Access | Times Cited: 9
A novel transfer learning fault diagnosis method for rolling bearing based on feature correlation matching
Bo Wang, Baoqiang Wang, Yi Ning
Measurement Science and Technology (2022) Vol. 33, Iss. 12, pp. 125006-125006
Closed Access | Times Cited: 15
Rolling bearing fault diagnosis under time-varying speeds based on time-characteristic order spectrum and multi-scale domain adaptation network
Zhenli Xu, Guiji Tang, Bin Pang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 12, pp. 125118-125118
Closed Access | Times Cited: 7
Few-shot condition diagnosis of rolling bearing using adversarial transfer network with class aggregation-guided
Shaoning Tian, Dong Zhen, Guohua Sun, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 6, pp. 066120-066120
Closed Access | Times Cited: 2
Rolling bearing fault diagnosis method based on multi-information fusion characteristics under complex working conditions
Xiaoyan Duan, Linlin Xue, Chunli Lei, et al.
Applied Acoustics (2023) Vol. 214, pp. 109685-109685
Closed Access | Times Cited: 6
A fault mechanism-based model for bearing fault diagnosis under non-stationary conditions without target condition samples
Hongchun Sun, Sheng Gao, Sihan Ma, et al.
Measurement (2022) Vol. 199, pp. 111499-111499
Closed Access | Times Cited: 8
Alleviating confirmation bias in perpetually dynamic environments: Continuous unsupervised domain adaptation-based condition monitoring (CUDACoM)
Mohamed Abubakr, Chi-Guhn Lee
Engineering Applications of Artificial Intelligence (2024) Vol. 137, pp. 109057-109057
Open Access | Times Cited: 1
Rolling Bearing Fault Diagnosis in Agricultural Machinery Based on Multi-Source Locally Adaptive Graph Convolution
Fengyun Xie, Enguang Sun, Linglan Wang, et al.
Agriculture (2024) Vol. 14, Iss. 8, pp. 1333-1333
Open Access | Times Cited: 1
Synthetic to Real Framework based on Convolutional Multi-Head Attention and Hybrid Domain Alignment
Mohammadreza Ghorvei, Mohammadreza Kavianpour, Mohammad Taghi Hamidi Beheshti, et al.
(2022), pp. 1-6
Closed Access | Times Cited: 7
A New Probability Guided Domain Adversarial Network for Bearing Fault Diagnosis
Jingde Li, Bojian Chen, Changqing Shen, et al.
IEEE Sensors Journal (2022) Vol. 23, Iss. 2, pp. 1462-1470
Closed Access | Times Cited: 7
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