1 citations · 1 across the 2 of their papers we have counts for
2 papers
eess.SP2024
Rolling bearing fault diagnosis method based on generative adversarial enhanced multi-scale convolutional neural network model
Maoxuan Zhou, Wei Kang, Kun He
In order to solve the problem that current convolutional neural networks can not capture the correlation features between the time domain signals of rolling bearings effectively, a…
cs.LG2023★ 1 cited
Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding
Jixuan Cui, Jun Li, Zhen Mei +5
Deep learning-based fault diagnosis (FD) approaches require a large amount of training data, which are difficult to obtain since they are located across different entities. Federat…