An autoencoder ... Convolutional Neural Network or fully-connected feedforward neural networks. An autoencoder has three main parts: An encoder that maps the input into the code. A decoder that maps ...

In this article, we will define a Convolutional Autoencoder in PyTorch and train it on the CIFAR-10 dataset in the CUDA environment to create reconstructed images. Convolutional Autoencoder is a ...

We propose a new framework to perform VS in the latent space learned by a convolutional autoencoder. We show that this latent space avoids explicit feature extraction and tracking issues and provides ...

Abstract: Whole brain tractography data contain a large number of streamlines that require algorithms such as clustering to group the data into smaller sets for visualization ... based on the latent ...