Learn about the most common and effective autoencoder variants for dimensionality reduction, and how they differ in structure, loss function, and application.

A new hierarchical convolutional neural network-based autoencoder architecture called SEHAE (Speech Enhancement Hierarchical AutoEncoder) is introduced, in which the latent representation is ...

This paper analyses the challenge of using the same autoencoder model for lossy compression on different hyperspectral sensors and its impact on the complex application of camouflaged target detection ...

The diagram in Figure 2 illustrates a neural autoencoder. The autoencoder has the same number of inputs and outputs (9) as the demo program, but for simplicity the illustrated autoencoder has ...

Network Architecture The overall architecture diagram of our proposed multiscale spatial–spectral Transformer network. The architecture diagram of the masked patches autoencoder. The architecture ...