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Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.

R. Wang, W. Huang, J. Wang, C. Ding, C. Shen, and Z. Zhu. IEEE Trans. Instrum. Meas., (2023)

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Changqing Zhao

Changqing Chen

Qi Changqing

Changqing Qi

Wei Shen

Other publications of authors with the same name

Graph embedding deep broad learning system for data imbalance fault diagnosis of rotating machinery.M. Shi, C. Ding, R. Wang, C. Shen, W. Huang, and Z. Zhu. Reliab. Eng. Syst. Saf., (December 2023)Sparse representation of gearbox compound fault features by combining Majorization-Minimization algorithm and wavelet bases.C. Luo, C. Shen, W. You, W. Huang, G. Cai, and Z. Zhu. I2MTC, page 1-5. IEEE, (2016)Fault Feature Extractor Based on Bootstrap Your Own Latent and Data Augmentation Algorithm for Unlabeled Vibration Signals.T. Peng, C. Shen, S. Sun, and D. Wang. IEEE Trans. Ind. Electron., 69 (9): 9547-9555 (2022)A New Incremental Learning for Bearing Fault Diagnosis Under Noisy Conditions Using Classification and Feature-Level Information.J. Zhu, Y. Wang, C. Huang, C. Shen, and B. Chen. IEEE Trans. Instrum. Meas., (2024)Federated contrastive prototype learning: An efficient collaborative fault diagnosis method with data privacy.R. Wang, W. Huang, X. Zhang, J. Wang, C. Ding, and C. Shen. Knowl. Based Syst., (December 2023)Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy.R. Wang, W. Huang, M. Shi, J. Wang, C. Shen, and Z. Zhu. Knowl. Based Syst., (2022)Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis.M. Shi, C. Ding, R. Wang, Q. Song, C. Shen, W. Huang, and Z. Zhu. Knowl. Based Syst., (2023)Multi-source Unsupervised Domain Adaptation for Machinery Fault Diagnosis under Different Working Conditions.J. Zhu, N. Chen, C. Shen, and D. Wang. INDIN, page 755-762. IEEE, (2020)Semi-supervised class incremental broad network for continuous diagnosis of rotating machinery faults with limited labeled samples.M. Shi, C. Ding, R. Wang, C. Shen, W. Huang, and Z. Zhu. Knowl. Based Syst., (2024)Adaptive Morphological Feature Extraction and Support Vector Regressive Classification for Gearbox Fault Diagnosis.Y. Qi, C. Shen, J. Shi, W. Huang, and Z. Zhu. AIM, page 868-872. IEEE, (2019)

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Disambiguation of "Shen, Changqing"

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Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.

Please choose a person to relate this publication to

Changqing Zhao

Changqing Chen

Qi Changqing

Changqing Qi

Wei Shen

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Shen, Changqing"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.

Please choose a person to relate this publication to

Changqing Zhao

Changqing Chen

Qi Changqing

Changqing Qi

Wei Shen

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.