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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:

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

Showing 26-50 of 164 citing articles:

A novel meta-learning approach for few-shot short-term wind power forecasting
Fuhao Chen, Jie Yan, Yongqian Liu, et al.
Applied Energy (2024) Vol. 362, pp. 122838-122838
Closed Access | Times Cited: 12
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis
Xiao Zhang, Weiguo Huang, Chuancang Ding, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102538-102538
Closed Access | Times Cited: 12
Few-shot classification of ultrasound breast cancer images using meta-learning algorithms
Gültekin Işık, İshak Paçal
Neural Computing and Applications (2024) Vol. 36, Iss. 20, pp. 12047-12059
Open Access | Times Cited: 12
SSPENet: Semi-supervised prototype enhancement network for rolling bearing fault diagnosis under limited labeled samples
Xuejian Yao, Xingchi Lu, Quan Jiang, et al.
Advanced Engineering Informatics (2024) Vol. 61, pp. 102560-102560
Closed Access | Times Cited: 11
Meta-learning with deep flow kernel network for few shot cross-domain remaining useful life prediction
Jing Yang, Xiaomin Wang
Reliability Engineering & System Safety (2024) Vol. 244, pp. 109928-109928
Closed Access | Times Cited: 10
A novel semi-supervised prototype network with two-stream wavelet scattering convolutional encoder for TBM main bearing few-shot fault diagnosis
Xingchen Fu, Jianfeng Tao, Keming Jiao, et al.
Knowledge-Based Systems (2024) Vol. 286, pp. 111408-111408
Closed Access | Times Cited: 9
Few-shot fault diagnosis of rolling bearing under variable working conditions based on ensemble meta-learning
Changchang Che, Huawei Wang, Minglan Xiong, et al.
Digital Signal Processing (2022) Vol. 131, pp. 103777-103777
Closed Access | Times Cited: 33
Fault Diagnosis for Limited Annotation Signals and Strong Noise Based on Interpretable Attention Mechanism
Biao Chen, Tingting Liu, Chao He, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 12, pp. 11865-11880
Closed Access | Times Cited: 31
Twin robust matrix machine for intelligent fault identification of outlier samples in roller bearing
Haiyang Pan, Haifeng Xu, Jinde Zheng, et al.
Knowledge-Based Systems (2022) Vol. 252, pp. 109391-109391
Closed Access | Times Cited: 30
A new meta-transfer learning method with freezing operation for few-shot bearing fault diagnosis
Peiqi Wang, Jingde Li, Shubei Wang, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 7, pp. 074005-074005
Closed Access | Times Cited: 21
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
Anomaly detection using a model-agnostic meta-learning-based variational auto-encoder for facility management
Jaeuk Moon, Yoona Noh, Seungwon Jung, et al.
Journal of Building Engineering (2023) Vol. 68, pp. 106099-106099
Closed Access | Times Cited: 18
Class-incremental continual learning model for plunger pump faults based on weight space meta-representation
Siyuan Liu, Jinying Huang, Jiancheng Ma, et al.
Mechanical Systems and Signal Processing (2023) Vol. 196, pp. 110309-110309
Closed Access | Times Cited: 17
A novel lightweight relation network for cross-domain few-shot fault diagnosis
Tang Tang, Chuanhang Qiu, Tianyuan Yang, et al.
Measurement (2023) Vol. 213, pp. 112697-112697
Closed Access | Times Cited: 16
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
Meta-learning-based approach for tool condition monitoring in multi-condition small sample scenarios
Bowen Zhang, Xianli Liu, Caixu Yue, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111444-111444
Closed Access | Times Cited: 6
Task-specific alignment and multiple-level transformer for few-shot action recognition
Fei Guo, Zhu Li, YiKang Wang, et al.
Neurocomputing (2024) Vol. 598, pp. 128044-128044
Open Access | Times Cited: 6
Prior Knowledge-Augmented Meta-Learning for Fine-Grained Fault Diagnosis
Yuhang Zhou, Qiang Zhang, Ting Huang, et al.
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 6, pp. 8115-8124
Closed Access | Times Cited: 5
A Semi-supervised Gaussian Mixture Variational Autoencoder method for few-shot fine-grained fault diagnosis
Zhiqian Zhao, Yeyin Xu, Jiabin Zhang, et al.
Neural Networks (2024) Vol. 178, pp. 106482-106482
Closed Access | Times Cited: 5
A novel meta-learning network with adversarial domain-adaptation and attention mechanism for cross-domain for train bearing fault diagnosis
Hao Zhong, Deqiang He, Zexian Wei, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 12, pp. 125109-125109
Closed Access | Times Cited: 5
A task-oriented theil index-based meta-learning network with gradient calibration strategy for rotating machinery fault diagnosis with limited samples
Mingzhe Mu, Hongkai Jiang, Xin Wang, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102870-102870
Closed Access | Times Cited: 5
CDCNet: Cross-domain few-shot learning with adaptive representation enhancement
Xueying Li, Zihang He, Lingyan Zhang, et al.
Pattern Recognition (2025), pp. 111382-111382
Closed Access
A meta-learning method based on meta-feature enhancement for bearing fault identification under few-sample conditions
Xianze Li, Guopeng Zhu, Aijun Hu, et al.
Mechanical Systems and Signal Processing (2025) Vol. 226, pp. 112370-112370
Closed Access
Improving global soil moisture prediction based on Meta-Learning model leveraging Köppen-Geiger climate classification
Qingliang Li, Xiaochun Jin, Cheng Zhang, et al.
CATENA (2025) Vol. 250, pp. 108743-108743
Closed Access
Unlocking the power of knowledge for few-shot fault diagnosis: A review from a knowledge perspective
Pei Ling Lai, Fan Zhang, Tianrui Li, et al.
Information Sciences (2025), pp. 121996-121996
Closed Access

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