IEEE

Convolutional Autoencoder With Sequential and Channel Attention for Robust ECG Signal Denoising With Edge Device Implementation

Abstract: Electrocardiograms (ECG) are vital for diagnosing various cardiac conditions but are often corrupted by noise from multiple sources, which can hinder accurate interpretation. Denoising ECG ...
Travel + Leisure

Florida's Incredible New High-speed Train Now Goes From Orlando to Miami — and I Was One of the First on Board

As Brightline’s self-proclaimed No. 1 fan, I’ve been waiting impatiently for its Orlando extension. Being a travel writer and central Florida native living in West Palm Beach, I feel like this modern ...
GitHub

Transformer-based Denoising AutoEncoder for Sentence Transformers Unsupervised pre-training

The acquisition of sentence embeddings often necessitates a substantial volume of labeled data. However, in many cases and fields, labeled data is rarely accessible, and the procurement of such data ...
IEEE

Elimination of Random Mixed Noise in ECG Using Convolutional Denoising Autoencoder With Transformer Encoder

Abstract: Electrocardiogram (ECG) signals frequently encounter diverse types of noise, such as baseline wander (BW), electrode motion (EM) artifacts, muscle artifact (MA), and others. These noises ...
GitHub

scVAG: Unified Single-Cell Clustering via Variational-Autoencoder Integration with Graph Attention Autoencoder

scVAG is an innovative framework that integrates Variational Autoencoder (VAE) and Graph Attention Autoencoder (GATE) models for enhanced analysis of single-cell gene expression data. Built upon the ...