To address this issue, we propose a novel hyperspectral anomaly detection method based on a spatial-spectral joint mask variational autoencoder (VAE). By combining the probabilistic modeling ...

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 ...

An autoencoder is an unsupervised neural network that learns to encode and reconstruct input images, making it useful for identifying outliers or anomalies. image-anomaly-with-autoencoder.ipynb → ...

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 ...

LLC (BEA), offering the opportunity for SRV to enter into a license and/or collaborative research agreement to commercialize this variational autoencoder for network anomaly detection. This ...