In intelligent fault diagnosis, transfer learning can reduce the requirement of sufficient labeled data and the same data distribution. However, for the diagnosis of a new machine, there are still ...

Deep Learning on Fashion MNIST: CNN Transfer Learning with Autoencoder. This notebook begins by setting up the Fashion MNIST dataset using TensorFlow. The notebook installs TensorFlow and loads the ...

Keywords: variational autoencoder (VAE), adversarial regularization, cross-subject transfer learning, mild TBI (mTBI), LSTM-long short-term memory Citation: Salsabilian S and Najafizadeh L (2022) ...

In this project, there are implementations for various kinds of autoencoders. The base python class is library/Autoencoder.py, you can set the value of "ae_para" in the construction function of ...

And there are specialized techniques for working with specific types of data, such as fraud detection systems. That said, applying a neural autoencoder anomaly detection system to tabular data is ...

In intelligent fault diagnosis, transfer learning can reduce the requirement of sufficient labeled data and the same data distribution. However, for the diagnosis of a new machine, there are still ...