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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 Learning-Based Bearing Fault Diagnosis Using a Trusted Multiscale Quadratic Attention-Embedded Convolutional Neural Network
Yuheng Tang, Chaoyong Zhang, Jianzhao Wu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-15
Closed Access | Times Cited: 19

Showing 19 citing articles:

Deep learning based multimodal biomedical data fusion: An overview and comparative review
Junwei Duan, Jiaqi Xiong, Yinghui Li, et al.
Information Fusion (2024) Vol. 112, pp. 102536-102536
Closed Access | Times Cited: 32
Classifier-guided neural blind deconvolution: A physics-informed denoising module for bearing fault diagnosis under noisy conditions
Jing-Xiao Liao, Chao He, Jipu Li, et al.
Mechanical Systems and Signal Processing (2024) Vol. 222, pp. 111750-111750
Closed Access | Times Cited: 6
MCRCNet: A Bearing Fault Diagnosis Method for Unknown Faults Based on Transfer Learning
Guangyuan Xu, Ruifeng Guo, Zhenyu Yin, et al.
Applied Sciences (2025) Vol. 15, Iss. 2, pp. 921-921
Open Access
KDN: A class-added continual learning framework for cross-machine fault diagnosis with limited samples
Jipu Li, Ke Yue, Zhaoqian Wu, et al.
Mechanical Systems and Signal Processing (2025) Vol. 227, pp. 112379-112379
Closed Access
A novel adaptive gating neurons model with physical features weighted for bearing fault diagnosis under strong noise
Panpan Guo, Weiguo Huang, Ning Jia, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110532-110532
Closed Access
Recognition of rolling bearing life status based on GI performance degradation indicator and AGNCN
Panpan Guo, Weiguo Huang, Xiao Zhang, et al.
Measurement (2025), pp. 117323-117323
Closed Access
A new cross-domain bearing fault diagnosis method with few samples under different working conditions
Xingjun Dong, Changsheng Zhang, Hanrui Liu, et al.
Journal of Manufacturing Processes (2025) Vol. 135, pp. 359-374
Closed Access
Interpretable quadratic convolutional residual neural network for bearing fault diagnosis
Zhiyong Luo, Shuping Pan, Xin Dong, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2025) Vol. 47, Iss. 4
Closed Access
Fault Diagnosis Method for Centrifugal Pumps in Nuclear Power Plants Based on a Multi-Scale Convolutional Self-Attention Network
Chen Li, Xinkai Liu, Hang Wang, et al.
Sensors (2025) Vol. 25, Iss. 5, pp. 1589-1589
Open Access
Recursive prototypical network with coordinate attention: A model for few-shot cross-condition bearing fault diagnosis
Yonghua Jiang, Zengjie Qiu, Linjie Zheng, et al.
Applied Acoustics (2024) Vol. 231, pp. 110442-110442
Closed Access | Times Cited: 2
Probabilistic Uncertainty-Aware Decision Fusion of Neural Network for Bearing Fault Diagnosis
Atabak Mostafavi, Mohammad Siami, A. Friedmann, et al.
PHM Society European Conference (2024) Vol. 8, Iss. 1, pp. 10-10
Open Access
Less Redundancy: Deduplicating Cad Datasets for Efffcient Deep Learning
Zijian Zhang, Rubin Fan, Fazhi He, et al.
(2024)
Closed Access
A novel simulation-assisted transfer method for bearing unknown fault diagnosis
F Huang, Xianxin Li, Kai Zhang, et al.
Measurement Science and Technology (2024) Vol. 35, Iss. 10, pp. 106127-106127
Closed Access
SeqAttention-Net: Design of a Deep Neural Network for Bearing Fault Detection Based on Small Sample Datasets
Haifeng Fan, Chengliang Huang, Chao Ren
Lecture notes in computer science (2024), pp. 107-118
Closed Access
Multi-scale Joint Convolution Neural Network integrated CapsNet model for Machinery Fault Diagnosis
Huangkun Xing, Xingxing Jiang, Qiuyu Song, et al.
(2024), pp. 293-299
Closed Access
An Interpretable Hybrid Framework Combining Convolution Latent Vectors with Transformer based Attention Mechanism for Rolling Element Fault Detection and Classification
Ali Saeed, Muhammad Usman Akram, Muazzam Khan Khattak, et al.
Heliyon (2024) Vol. 10, Iss. 21, pp. e38993-e38993
Open Access
A multi-depth step-training convolutional neural network for power machinery fault diagnosis under variable loads
Jiewei Lin, Gou Xin, Xiaolong Zhu, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-14
Closed Access
DSTF-Net: A Novel Framework for Intelligent Diagnosis of Insulated Bearings in Wind Turbines with Multi-Source Data and Its Interpretability
Tongguang Yang, Ming Xu, Chun‐Lung Chen, et al.
Renewable Energy (2024), pp. 121965-121965
Closed Access
A Real-Time Downhole Fluid Identification System Empowered by Efficient Quadratic Neural Network
Zhongshuai Chen, Hongjian Ni, Xueliang Pei, et al.
Electronics (2024) Vol. 13, Iss. 24, pp. 5021-5021
Open Access
CMFE-PVT: A lightweight fault diagnosis framework for rolling bearings using compact multi-scale feature extraction and a pruned-restructured vision transformer
Shanshan Ding, Weibing Wu, Xiaolu Ma, et al.
Measurement Science and Technology (2024) Vol. 36, Iss. 2, pp. 025015-025015
Closed Access
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