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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:

Interpretable data-augmented adversarial variational autoencoder with sequential attention for imbalanced fault diagnosis
Yunpeng Liu, Hongkai Jiang, Renhe Yao, et al.
Journal of Manufacturing Systems (2023) Vol. 71, pp. 342-359
Closed Access | Times Cited: 21

Showing 21 citing articles:

Counterfactual-augmented few-shot contrastive learning for machinery intelligent fault diagnosis with limited samples
Yunpeng Liu, Hongkai Jiang, Renhe Yao, et al.
Mechanical Systems and Signal Processing (2024) Vol. 216, pp. 111507-111507
Closed Access | Times Cited: 32
Extended attention signal transformer with adaptive class imbalance loss for Long-tailed intelligent fault diagnosis of rotating machinery
Shuyuan Chang, Liyong Wang, Mingkuan Shi, et al.
Advanced Engineering Informatics (2024) Vol. 60, pp. 102436-102436
Closed Access | Times Cited: 18
A lightweight progressive joint transfer ensemble network inspired by the Markov process for imbalanced mechanical fault diagnosis
Changdong Wang, Jingli Yang, Huamin Jie, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 111994-111994
Closed Access | Times Cited: 15
An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples
Yutong Dong, Hongkai Jiang, Xin Wang, et al.
Reliability Engineering & System Safety (2024) Vol. 251, pp. 110404-110404
Closed Access | Times Cited: 13
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
Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects
Shen Liu, Jinglong Chen, Yong Feng, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124511-124511
Closed Access | Times Cited: 8
CycleGAN denoising of recurrence plots of rolling bearing vibration signals for improved fault classification
Thomas Joseph, U. Sudeep, K. Keerthi Krishnan
Journal of Mechanical Science and Technology (2025)
Closed Access
Wavelet-driven differentiable architecture search for planetary gear fault diagnosis
Yanghu Wang, Zheng Zhou, Laihao Yang, et al.
Journal of Manufacturing Systems (2024) Vol. 74, pp. 587-593
Closed Access | Times Cited: 4
Explainable AI (XAI) Techniques for Convolutional Neural Network-Based Classification of Drilled Holes in Melamine Faced Chipboard
Alexander Sieradzki, Jakub Bednarek, Albina Jegorowa, et al.
Applied Sciences (2024) Vol. 14, Iss. 17, pp. 7462-7462
Open Access | Times Cited: 4
Fault diagnosis method for imbalanced data based on adaptive diffusion models and generative adversarial networks
Xueyi Li, Xudong Wu, Tianyang Wang, et al.
Engineering Applications of Artificial Intelligence (2025) Vol. 147, pp. 110410-110410
Closed Access
Enhancing Reliability Through Interpretability: A Comprehensive Survey of Interpretable Intelligent Fault Diagnosis in Rotating Machinery
Gang Chen, Junlin Yuan, Yiyue Zhang, et al.
IEEE Access (2024) Vol. 12, pp. 103348-103379
Open Access | Times Cited: 3
Superpixel perception graph neural network for intelligent defect detection of aero-engine blade
Hongbing Shang, Qixiu Yang, Chuang Sun, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 112-126
Closed Access | Times Cited: 3
A numerical simulation enhanced multi-task integrated learning network for fault detection in rotation vector reducers
Hui Wang, Shuhui Wang, Ronggang Yang, et al.
Mechanical Systems and Signal Processing (2024) Vol. 217, pp. 111525-111525
Closed Access | Times Cited: 3
Deep discriminative sparse representation learning for machinery fault diagnosis
Renhe Yao, Hongkai Jiang, Wenxin Jiang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108836-108836
Closed Access | Times Cited: 2
Deep expert network: A unified method toward knowledge-informed fault diagnosis via fully interpretable neuro-symbolic AI
Qi Li, Yuekai Liu, Shilin Sun, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 652-661
Closed Access | Times Cited: 2
Advanced Data Augmentation Techniques for Enhanced Fault Diagnosis in Industrial Centrifugal Pumps
Dong-Yun Kim, Akeem Bayo Kareem, Daryl Domingo, et al.
Journal of Sensor and Actuator Networks (2024) Vol. 13, Iss. 5, pp. 60-60
Open Access | Times Cited: 1
A multi-channel fusion variational autoencoder-based RUL prediction approach for multi-sensor systems
Yuxiao Wang, Chao Suo, Yuyu Zhao
Measurement Science and Technology (2024) Vol. 35, Iss. 11, pp. 116129-116129
Closed Access
A Hierarchical Matrix Factorization-Based Method for Intelligent Industrial Fault Diagnosis
Yanxia Li, Han Zhou, Jiajia Liu, et al.
Sensors (2024) Vol. 24, Iss. 16, pp. 5408-5408
Open Access
Deep learning-based fault diagnosis of planetary gearbox: A systematic review
Hassaan Ahmad, Wei Cheng, Ji Xing, et al.
Journal of Manufacturing Systems (2024) Vol. 77, pp. 730-745
Closed Access
Transfer Learning‐Based Fault Diagnosis of Internal Combustion (IC) Engine Gearbox Using Radar Plots
Naveen Venkatesh Sridharan, B Srivatsan, V. Sugumaran, et al.
Journal of Sensors (2024) Vol. 2024, Iss. 1
Open Access
Perturbation-driven data augmentation for time series anomaly detection improvement in predictive maintenance
Hyeyoung Lee, Sangkyun Lee, Sungjoon Choi
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 1367-1372
Closed Access
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