Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis

Y Feng, J Chen, T Zhang, S He, E Xu, Z Zhou - ISA transactions, 2022 - Elsevier
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …
被引用次数：132 相关文章

Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis

Y Feng, J Chen, T Zhang, S He, E Xu… - ISA …, 2022 - pubmed.ncbi.nlm.nih.gov
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …

Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis.

Y Feng, J Chen, T Zhang, S He, E Xu, Z Zhou - ISA Transactions, 2021 - europepmc.org
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …

Semi-supervised meta-learning networks with squeeze-and-excitation attention for few-shot fault diagnosis

Y Feng, J Chen, T Zhang, S He, E Xu, Z Zhou - ISA Transactions, 2022 - Elsevier
In the engineering practice, lacking of data especially labeled data typically hinders the wide
application of deep learning in mechanical fault diagnosis. However, collecting and labeling …