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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:

Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data
Liang Guo, Yaguo Lei, Saibo Xing, et al.
IEEE Transactions on Industrial Electronics (2018) Vol. 66, Iss. 9, pp. 7316-7325
Closed Access | Times Cited: 988

Showing 26-50 of 988 citing articles:

A Polynomial Kernel Induced Distance Metric to Improve Deep Transfer Learning for Fault Diagnosis of Machines
Bin Yang, Yaguo Lei, Feng Jia, et al.
IEEE Transactions on Industrial Electronics (2019) Vol. 67, Iss. 11, pp. 9747-9757
Closed Access | Times Cited: 207
Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning
Zhang We, Xiang Li, Hui Ma, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 12, pp. 7957-7967
Closed Access | Times Cited: 206
Unsupervised domain-share CNN for machine fault transfer diagnosis from steady speeds to time-varying speeds
Hongru Cao, Haidong Shao, Xiang Zhong, et al.
Journal of Manufacturing Systems (2021) Vol. 62, pp. 186-198
Closed Access | Times Cited: 206
Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning
Zhang We, Xiang Li, Hui Ma, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 11, pp. 7445-7455
Closed Access | Times Cited: 185
Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016
Xiaohan Chen, Rui Yang, Yihao Xue, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-21
Open Access | Times Cited: 185
Subdomain Adaptation Transfer Learning Network for Fault Diagnosis of Roller Bearings
Zhijian Wang, Xinxin He, Bin Yang, et al.
IEEE Transactions on Industrial Electronics (2021) Vol. 69, Iss. 8, pp. 8430-8439
Closed Access | Times Cited: 182
Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places
Xiang Li, Zhang We, Nan-Xi Xu, et al.
IEEE Transactions on Industrial Electronics (2019) Vol. 67, Iss. 8, pp. 6785-6794
Closed Access | Times Cited: 181
Data-Driven Fault Diagnosis Method Based on Compressed Sensing and Improved Multiscale Network
Zhongxu Hu, Yan Wang, Ming‐Feng Ge, et al.
IEEE Transactions on Industrial Electronics (2019) Vol. 67, Iss. 4, pp. 3216-3225
Open Access | Times Cited: 180
A double-layer attention based adversarial network for partial transfer learning in machinery fault diagnosis
Yafei Deng, Delin Huang, Shichang Du, et al.
Computers in Industry (2021) Vol. 127, pp. 103399-103399
Closed Access | Times Cited: 178
A Survey of Predictive Maintenance: Systems, Purposes and Approaches
Yongyi Ran, Xin Zhou, Pengfeng Lin, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 176
Residual joint adaptation adversarial network for intelligent transfer fault diagnosis
Jinyang Jiao, Ming Zhao, Jing Lin, et al.
Mechanical Systems and Signal Processing (2020) Vol. 145, pp. 106962-106962
Closed Access | Times Cited: 172
Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics
Xiang Li, Zhang We
IEEE Transactions on Industrial Electronics (2020) Vol. 68, Iss. 5, pp. 4351-4361
Closed Access | Times Cited: 169
Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis
Minghang Zhao, Shisheng Zhong, Xuyun Fu, et al.
IEEE Transactions on Industrial Electronics (2020) Vol. 68, Iss. 3, pp. 2587-2597
Closed Access | Times Cited: 165
Cross-Domain Fault Diagnosis Using Knowledge Transfer Strategy: A Review
Huailiang Zheng, Rixin Wang, Yuantao Yang, et al.
IEEE Access (2019) Vol. 7, pp. 129260-129290
Open Access | Times Cited: 164
A Two-Stage Transfer Adversarial Network for Intelligent Fault Diagnosis of Rotating Machinery With Multiple New Faults
Jipu Li, Ruyi Huang, Guolin He, et al.
IEEE/ASME Transactions on Mechatronics (2020) Vol. 26, Iss. 3, pp. 1591-1601
Open Access | Times Cited: 161
A Novel Weighted Adversarial Transfer Network for Partial Domain Fault Diagnosis of Machinery
Weihua Li, Zhuyun Chen, Guolin He
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 3, pp. 1753-1762
Closed Access | Times Cited: 160
Condition Monitoring Based on Partial Discharge Diagnostics Using Machine Learning Methods: A Comprehensive State-of-the-Art Review
Shibo Lu, Hua Chai, Animesh Sahoo, et al.
IEEE Transactions on Dielectrics and Electrical Insulation (2020) Vol. 27, Iss. 6, pp. 1861-1888
Closed Access | Times Cited: 159
Unsupervised cross-domain rolling bearing fault diagnosis based on time-frequency information fusion
Hongfeng Tao, Jier Qiu, Yiyang Chen, et al.
Journal of the Franklin Institute (2022) Vol. 360, Iss. 2, pp. 1454-1477
Closed Access | Times Cited: 157
Joint distribution adaptation network with adversarial learning for rolling bearing fault diagnosis
Ke Zhao, Hongkai Jiang, Kaibo Wang, et al.
Knowledge-Based Systems (2021) Vol. 222, pp. 106974-106974
Closed Access | Times Cited: 155
Metric-based meta-learning model for few-shot fault diagnosis under multiple limited data conditions
Duo Wang, Ming Zhang, Yuchun Xu, et al.
Mechanical Systems and Signal Processing (2021) Vol. 155, pp. 107510-107510
Open Access | Times Cited: 154
Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions
Te Han, Chao Liu, Wenguang Yang, et al.
ISA Transactions (2019) Vol. 93, pp. 341-353
Closed Access | Times Cited: 151
Joint Activity Recognition and Indoor Localization With WiFi Fingerprints
Fei Wang, Jianwei Feng, Yinliang Zhao, et al.
IEEE Access (2019) Vol. 7, pp. 80058-80068
Open Access | Times Cited: 149
Collaborative fault diagnosis of rotating machinery via dual adversarial guided unsupervised multi-domain adaptation network
Xingkai Chen, Haidong Shao, Yiming Xiao, et al.
Mechanical Systems and Signal Processing (2023) Vol. 198, pp. 110427-110427
Open Access | Times Cited: 149
Data alignments in machinery remaining useful life prediction using deep adversarial neural networks
Xiang Li, Zhang We, Hui Ma, et al.
Knowledge-Based Systems (2020) Vol. 197, pp. 105843-105843
Closed Access | Times Cited: 147
A New Multiple Source Domain Adaptation Fault Diagnosis Method Between Different Rotating Machines
Jun Zhu, Nan Chen, Changqing Shen
IEEE Transactions on Industrial Informatics (2020) Vol. 17, Iss. 7, pp. 4788-4797
Closed Access | Times Cited: 147

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