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 intelligent diagnosis method of rolling bearing based on multi-scale residual shrinkage convolutional neural network
Xiaoqiang Zhao, Yazhou Zhang
Measurement Science and Technology (2022) Vol. 33, Iss. 8, pp. 085103-085103
Closed Access | Times Cited: 15

Showing 15 citing articles:

A review of the application of deep learning in intelligent fault diagnosis of rotating machinery
Zhiqin Zhu, Yangbo Lei, Guanqiu Qi, et al.
Measurement (2022) Vol. 206, pp. 112346-112346
Closed Access | Times Cited: 283

An Intelligent Fault Diagnosis Method of Rolling Bearings Based on Short-Time Fourier Transform and Convolutional Neural Network
Qi Zhang, Linfeng Deng
Journal of Failure Analysis and Prevention (2023) Vol. 23, Iss. 2, pp. 795-811
Closed Access | Times Cited: 55

Data privacy protection: A novel federated transfer learning scheme for bearing fault diagnosis
Lilan Liu, Zhenhao Yan, Tingting Zhang, et al.
Knowledge-Based Systems (2024) Vol. 291, pp. 111587-111587
Open Access | Times Cited: 8

Fatigue crack identification in jacket-type offshore platforms using a parallel multi-scale convolutional neural network
Feng Shi, Lei Song, Zhuoyi Yang, et al.
Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment (2025)
Closed Access

A novel fault diagnosis approach of rolling bearing using intrinsic feature extraction and CBAM-enhanced InceptionNet
Shijie Xu, Rui Yuan, Yong Lv, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 10, pp. 105111-105111
Closed Access | Times Cited: 13

LGMA-DRSN: a lightweight convex global multi-attention deep residual shrinkage network for fault diagnosis
Zhijin Zhang, Chunlei Zhang, Lei Chen, et al.
Measurement Science and Technology (2023) Vol. 34, Iss. 11, pp. 115011-115011
Closed Access | Times Cited: 5

Rolling bearing fault diagnosis model based on DSCB-NFAM
Xiaoqiang Zhao, Haike Guo
Measurement Science and Technology (2023) Vol. 35, Iss. 1, pp. 015029-015029
Closed Access | Times Cited: 5

Multiscale dilated convolution and swin-transformer for small sample gearbox fault diagnosis
Yazhou Zhang, Xiaoqiang Zhao, Haopeng Liang, et al.
Applied Intelligence (2024) Vol. 54, Iss. 17-18, pp. 7716-7732
Closed Access | Times Cited: 1

Multi-scale Deep Subspace Clustering Network with Hierarchical Fusion Mechanism for Mechanical Fault Diagnosis
Gang Wang, Mingfeng Lu
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 1

An Intelligent diagnosis method for rolling bearings based on Ghost module and adaptive weighting module
Qiang Ruiru, Xiaoqiang Zhao
Multimedia Tools and Applications (2024)
Closed Access

Road terrain recognition based on tire noise for autonomous vehicle
Dongsheng Yang, Dongmin Zhang, Yi Yuan, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access

Bearing Fault diagnosis based on convolution Neural Network with Multi-Attention Mechanism
Yuhan Mao, Xianghui Liao
(2023), pp. 210-214
Closed Access | Times Cited: 1

A dual attention module and convolutional neural network based bearing fault diagnosis
Yazhou Zhang
Journal of Electronics and Information Science (2022) Vol. 7, Iss. 3
Open Access | Times Cited: 1

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