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 ...
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 ...
As an important part of active sonar, transmitted signals have a great influence on the performance of ocean exploration, however, in the actual environment, due to the existence of the Doppler ...
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 ...
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 ...
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