Therefore, this paper focuses on developing a cyber anomaly detection based on an autoencoder neural network that is an unsupervised learning approach. The autoencoder neural network is generally ...

The demo program presented in this article uses image data, but the autoencoder anomaly detection technique can work with any type of data. The demo begins by creating a Dataset object that stores the ...

A deep learning framework for unsupervised anomaly detection in time series data using autoencoder architectures. The initial implementation uses a convolutional autoencoder (CAE) model, as shown in ...

Nejad The initial implementation uses a convolutional autoencoder (CAE) model, as shown in Fig. 1, trained on electrical and electromagnetic time series data for anomaly detection in wind turbine ...