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 ...
Modern image and video generation methods rely heavily on tokenization to encode high-dimensional data into compact latent representations. While advancements in scaling generator models have been ...
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: In the realm of surveillance systems, ensuring robust anomaly detection capabilities is crucial for safeguarding against potential security breaches or hazardous incidents. This work uses ...
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