IEEE

Unsupervised Representation Learning and Explainable Clustering for Wafer Map Pattern Analysis

Abstract: As wafer maps become increasingly complex and high-dimensional, conventional clustering methods often fail to uncover subtle but meaningful defect patterns critical for yield enhancement and ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
Frontiers

A multi-graph convolutional network method for Alzheimer’s disease diagnosis based on multi-frequency EEG data with dual-mode connectivity

Objective: Alzheimer’s disease (AD) is mainly identified by cognitive function deterioration. Diagnosing AD at early stages poses significant challenges for both researchers and healthcare ...
AZoSensors

AI Maps Heat Inside Steelmaking’s Critical Sintering Process Beds

The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...
Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...
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 ...
GitHub

This project contains a TensorFlow-based Denoising Autoencoder (DAE) to exact model galaxy from observed galaxy images and perform galaxy model subtraction.

Clone this repository to your local machine or cloud service using the following command: To provide a comprehensive overview of the dataset generation process used in your project, it's important to ...