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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:

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

Showing 9 citing articles:

MRCFN: A multi-sensor residual convolutional fusion network for intelligent fault diagnosis of bearings in noisy and small sample scenarios
Maoyou Ye, Xiaoan Yan, Xing Hua, et al.
Expert Systems with Applications (2024) Vol. 259, pp. 125214-125214
Closed Access | Times Cited: 11
Normalization-Guided and Gradient-Weighted Unsupervised Domain Adaptation Network for Transfer Diagnosis of Rolling Bearing Faults Under Class Imbalance
Hao Luo, Xinyue Wang, Li Zhang
Actuators (2025) Vol. 14, Iss. 1, pp. 39-39
Open Access
Multi-scale quadratic convolutional neural network for bearing fault diagnosis based on multi-sensor data fusion
Yingying Ji, Jun Gao, Xing Shao, et al.
Nonlinear Dynamics (2025)
Closed Access
Novel Adversarial Unsupervised Subdomain Adaption Multi-Channel Deep Convolutional Network for Cross-Operating Fault Diagnosis of Rolling Bearings
B. Zhang, Tianlong Huo, Zheng Liu, et al.
IEEE Access (2024) Vol. 12, pp. 42068-42082
Open Access | Times Cited: 3
A novel multi-scale convolutional neural network incorporating multiple attention mechanisms for bearing fault diagnosis
Baoquan Hu, Jun Liu, Yue Xu
Measurement (2024) Vol. 242, pp. 115927-115927
Closed Access | Times Cited: 3
Multi-source domain adversarial graph convolutional networks for rolling mill health states diagnosis under variable working conditions
Shuai Zhao, Leping Bao, Changhui Hou, et al.
Structural Health Monitoring (2024) Vol. 23, Iss. 6, pp. 3505-3524
Closed Access | Times Cited: 1
A hybrid dynamic adversarial domain adaptation network with multi-channel attention mechanism for rotating machinery unsupervised fault diagnosis under varying operating conditions
Hangbo Duan, Zongyan Cai, Yuanbo Xu
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science (2024) Vol. 238, Iss. 21, pp. 10566-10577
Closed Access | Times Cited: 1
Local fusion generative adversarial network with dual-discriminator and parallel multipath and its application in machinery fault diagnosis with imbalanced data
Miao Ju, Chuancang Ding, Weiguo Huang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116135-116135
Closed Access
Bearing Fault Diagnosis via Graph Autoencoder Networks with Multi-kernel Subdomain Adversarial Domain Adaptation
Junfeng Guo, HU Ze-ming, Zhiming Wang, et al.
Journal of Failure Analysis and Prevention (2024)
Closed Access
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