This image provides a complete visual guide to the autoencoder neural network, featuring five illustrations that detail each stage of the data encoding and decoding process. It serves as an ...

An autoencoder is a type of artificial neural network commonly used to learn efficient representations of data, typically for dimensionality reduction, data compression, or denoising (noise removal).

Similar to convolution neural networks, a convolutional autoencoder specializes in the learning of ... The Gaussian distribution is sampled to create a vector, which is fed into the decoding network, ...

A autoencoder is a neural network that has three layers: an input layer, a hidden (encoding) layer, and a decoding layer. The network is trained to reconstruct its inputs, which forces the hidden ...

In this paper, a novel local anomaly detection model DAGNN is proposed, which incorporates a graph neural network to better aggregate neighbors' distance information of each sample for forming its ...

The result shows among the methods (support vector machine, neural network with dropout, autoencoder), neural network with added layers with dropout has the highest accuracy. And a comparison with the ...