However, relatively little research has addressed open-set learning issues involving unknown working modes. A multifunction radar working mode open-set recognition method based on dual autoencoder ...

In complex industrial production environments, the efficacy of fault diagnostic techniques has become increasingly important and can enhance the reliability and safety of systems. In recent years, the ...

The autoencoder network model for HIV classification, proposed in this paper, thus outperforms the conventional feedforward neural network models and is a much better classifier.

we propose a Hierarchical ST variational autoencoder (HiSTaR) to extract multi-level latent features of spots. HiSTaR tends to perform well in identifying spatial domains across multiple datasets from ...

We present a novel granular computing approach that assesses landslide risk by combining fuzzy information granulation and a stacked autoencoder algorithm. The stacked autoencoder is trained using an ...