Dynamic Semi-Supervised Federated Learning Fault Diagnosis Method Based on an Attention Mechanism

In cases where a client suffers from completely unlabeled data, unsupervised learning has difficulty achieving an accurate fault diagnosis. Semi-supervised federated learning with the ability for interaction between a labeled client and an unlabeled client has been developed to overcome this difficu...

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Detalles Bibliográficos
Autores principales: Liu, Shun, Zhou, Funa, Tang, Shanjie, Hu, Xiong, Wang, Chaoge, Wang, Tianzhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606357/
https://www.ncbi.nlm.nih.gov/pubmed/37895591
http://dx.doi.org/10.3390/e25101470

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606357/
https://www.ncbi.nlm.nih.gov/pubmed/37895591
http://dx.doi.org/10.3390/e25101470

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