Latent Representation Learning: The multi-resolution features are fed into the VAE encoder to learn a probabilistic latent ... detection in crowded scenes by synergistically integrating Variational ...

In this article, we propose a self-augmentation strategy for improving ML-based device modeling using variational autoencoder (VAE)-based techniques. These techniques require a small number of ...

The number of neurons in the input and output layers is a fixed number of 4980 while the number of neurons in the encoder and decoder varies with the number of hidden layers. The dimension of the ...

A variational autoencoder (VAE) is a deep neural system that can be ... some liberties with terminology and details to help make the explanation digestible. The diagram in Figure 2 shows the ...

An autoencoder is a neural network that predicts its own input. The diagram in Figure 3 shows the architecture ... The first part of an autoencoder is called the encoder component, and the second part ...