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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:

Similarity-based meta-learning network with adversarial domain adaptation for cross-domain fault identification
Yong Feng, Jinglong Chen, Zhuozheng Yang, et al.
Knowledge-Based Systems (2021) Vol. 217, pp. 106829-106829
Closed Access | Times Cited: 80

Showing 1-25 of 80 citing articles:

A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges
Weihua Li, Ruyi Huang, Jipu Li, et al.
Mechanical Systems and Signal Processing (2021) Vol. 167, pp. 108487-108487
Open Access | Times Cited: 520
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Yong Feng, Jinglong Chen, Jingsong Xie, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107646-107646
Closed Access | Times Cited: 164
A novel method based on meta-learning for bearing fault diagnosis with small sample learning under different working conditions
Hao Su, Ling Xiang, Aijun Hu, et al.
Mechanical Systems and Signal Processing (2022) Vol. 169, pp. 108765-108765
Closed Access | Times Cited: 164
Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds
Jingjie Luo, Haidong Shao, Jian Lin, et al.
Reliability Engineering & System Safety (2024) Vol. 245, pp. 110001-110001
Closed Access | Times Cited: 89
Meta-learning approaches for learning-to-learn in deep learning: A survey
Yingjie Tian, Xiaoxi Zhao, Wei Huang
Neurocomputing (2022) Vol. 494, pp. 203-223
Closed Access | Times Cited: 79
Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions
Qi Li, Liang Chen, Lin Kong, et al.
Reliability Engineering & System Safety (2023) Vol. 234, pp. 109171-109171
Open Access | Times Cited: 65
Fault diagnosis in rotating machines based on transfer learning: Literature review
Iqbal Misbah, C.K.M. Lee, K. L. Keung
Knowledge-Based Systems (2023) Vol. 283, pp. 111158-111158
Closed Access | Times Cited: 57
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Mehdi Saman Azari, Francesco Flammini, Stefania Santini, et al.
IEEE Access (2023) Vol. 11, pp. 12887-12910
Open Access | Times Cited: 42
Advances and Challenges in Meta-Learning: A Technical Review
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 7, pp. 4763-4779
Open Access | Times Cited: 38
Small data challenges for intelligent prognostics and health management: a review
Chuanjiang Li, Shaobo Li, Yixiong Feng, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 23
Deep residual LSTM with domain-invariance for remaining useful life prediction across domains
Song Fu, Yongjian Zhang, Lin Lin, et al.
Reliability Engineering & System Safety (2021) Vol. 216, pp. 108012-108012
Closed Access | Times Cited: 82
Semi-supervised multi-scale attention-aware graph convolution network for intelligent fault diagnosis of machine under extremely-limited labeled samples
Zongliang Xie, Jinglong Chen, Yong Feng, et al.
Journal of Manufacturing Systems (2022) Vol. 64, pp. 561-577
Closed Access | Times Cited: 62
Contrastive-weighted self-supervised model for long-tailed data classification with vision transformer augmented
Rujie Hou, Jinglong Chen, Yong Feng, et al.
Mechanical Systems and Signal Processing (2022) Vol. 177, pp. 109174-109174
Closed Access | Times Cited: 42
One-stage self-supervised momentum contrastive learning network for open-set cross-domain fault diagnosis
Weicheng Wang, Chao Li, Aimin Li, et al.
Knowledge-Based Systems (2023) Vol. 275, pp. 110692-110692
Closed Access | Times Cited: 34
Multi-sensor open-set cross-domain intelligent diagnostics for rotating machinery under variable operating conditions
Yongchao Zhang, Jinchen Ji, Zhaohui Ren, et al.
Mechanical Systems and Signal Processing (2023) Vol. 191, pp. 110172-110172
Closed Access | Times Cited: 24
Cross-domain few-shot fault diagnosis based on meta-learning and domain adversarial graph convolutional network
Junwei Hu, Weigang Li, Yong Zhang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 136, pp. 108970-108970
Closed Access | Times Cited: 13
Uncertainty-based contrastive prototype-matching network towards cross-domain fault diagnosis with small data
Tian Zhang, Jinyang Jiao, Jing Lin, et al.
Knowledge-Based Systems (2022) Vol. 254, pp. 109651-109651
Closed Access | Times Cited: 32
Novel joint transfer fine-grained metric network for cross-domain few-shot fault diagnosis
Junwei Hu, Weigang Li, Ailong Wu, et al.
Knowledge-Based Systems (2023) Vol. 279, pp. 110958-110958
Closed Access | Times Cited: 19
Domain-invariant feature fusion networks for semi-supervised generalization fault diagnosis
He Ren, Jun Wang, Weiguo Huang, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 107117-107117
Closed Access | Times Cited: 18
Industrial Edge Intelligence: Federated-Meta Learning Framework for Few-Shot Fault Diagnosis
Jiao Chen, Jianhua Tang, Weihua Li
IEEE Transactions on Network Science and Engineering (2023), pp. 1-13
Closed Access | Times Cited: 16
Self-supervised feature learning for motor fault diagnosis under various torque conditions
Sang Kyung Lee, Hyeongmin Kim, Minseok Chae, et al.
Knowledge-Based Systems (2024) Vol. 288, pp. 111465-111465
Closed Access | Times Cited: 5
Transfer Learning for Prognostics and Health Management: Advances, Challenges, and Opportunities
Ruqiang Yan, Weihua Li, Siliang Lu, et al.
Journal of Dynamics Monitoring and Diagnostics (2024)
Open Access | Times Cited: 5
AI-powered trustable and explainable fall detection system using transfer learning
Aryan Nikul Patel, Ramalingam Murugan, Praveen Kumar Reddy Maddikunta, et al.
Image and Vision Computing (2024) Vol. 149, pp. 105164-105164
Closed Access | Times Cited: 5
Globally Localized Multisource Domain Adaptation for Cross-Domain Fault Diagnosis With Category Shift
Yong Feng, Jinglong Chen, Shuilong He, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 34, Iss. 6, pp. 3082-3096
Closed Access | Times Cited: 37
A multi-module generative adversarial network augmented with adaptive decoupling strategy for intelligent fault diagnosis of machines with small sample
Kaiyu Zhang, Qiang Chen, Jinglong Chen, et al.
Knowledge-Based Systems (2021) Vol. 239, pp. 107980-107980
Closed Access | Times Cited: 35
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