IEEE

Application of variational autoencoder network to real-time prediction of steel crown in the hot strip rolling mill process

Abstract: In the hot strip rolling mill (HSRM) process, accurate prediction and control of the strip crown are critical for quality assurance. In order to cope with this challenge, this study designed ...
GitHub

ti2ni1m/Image-Generation-with-Conditional-Variational-Autoencoder-C-VAE-and-Conditional-GAN-C-GAN-

In this project, I aim to create a set of images of Kuzushiji Japanese characters via the Kuzushiji-49 dataset using 2 graphical models which are Conditional-Variational Autoencoder(C-VAE), and ...
Frontiers

Accurate identification of snoRNA targets using variational graph autoencoder to advance the redevelopment of traditional medicines

Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) is closely associated with various diseases, including lung cancer. Furthermore, these diseases ...
GitHub

MRI Tumor Detection Using Triplet Variational Autoencoder

This repository contains the implementation of a Triplet Variational Autoencoder (Tri-VAE) designed to detect anomalies in brain MRI scans. The method is inspired by the CVPR 2024 paper: "Triplet ...
IEEE

Convolutional Variational Autoencoder for Anomaly Detection in On-Load Tap Changers

Abstract: Transformer outages significantly impact the reliability and cost efficiency of power systems. Studies indicate that approximately 30% of transformer failures stem from issues with on-load ...