An autoencoder is a type of unsupervised neural network that learns to represent input data in a compressed latent space. This compressed representation captures the essential features of the data ...

This project will introduce the Variational Auto Encoder for processing images, using CelebA dataset in Python. The aim of this project is to introduce the Variational Auto Encoder, both theoretically ...

Manifold learning, rooted in the manifold assumption, reveals low-dimensional structures within input data, positing that the data exists on a low-dimensional manifold within a high-dimensional ...

1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...

Artificial neural networks (ANN) have gained significant attention in magnetotelluric (MT) inversions due to their ability to generate rapid inversion results compared to traditional methods. While a ...

Abstract: A Tuberculosis (TB) is an infectious disease caused by the Mycobacterium that can be prevented and treated. The TB automatic identification as an AI tool can help physicians to see the TB ...

Abstract: Power quality issues are required to be addressed properly in forthcoming era of smart meters, smart grids and increase in renewable energy integration. In this paper, Deep Auto-encoder (DAE ...