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 ...
Simon Fraser University

Interactive Reconstruction of Monte Carlo Image Sequences using a Recurrent Denoising Autoencoder

Owing to the immense popularity of ray-tracing and path tracing rendering algorithms for visual effects, there has been a surge of interest in developing filtering and reconstruction methods to deal ...
GitHub

CONVOLUTIONAL-AUTOENCODER-FOR-IMAGE-DENOISING

This code implements a Denoising Autoencoder using PyTorch to clean noisy images from the MNIST dataset. It uses a convolutional neural network architecture, where the encoder compresses the input ...
IEEE

Attention-Based Convolutional Denoising Autoencoder for Two-Lead ECG Denoising and Arrhythmia Classification

Abstract: This article presents a fast and accurate electrocardiogram (ECG) denoising and classification method for low-quality ECG signals. To achieve this, a novel attention-based convolutional ...
IEEE

Denoising Autoencoder for ECG Signals Based on Frequency Domain Alignment and Multi-Scale Transformer

Abstract: Electrocardiogram (ECG) signals are widely utilized for cardiovascular disease monitoring. However, these signals are often susceptible to various types of noise during acquisition, which ...
Europe PMC

SADA: An advanced Spectral Attention Denoising Autoencoder for high-fidelity and efficient infrared spectral data generation.

This study utilizes a Fourier transform infrared spectroscopy (FTIR)-based detection system to obtain and analyze the infrared spectra of cigarette smoke aerosols. To reduce the workload of spectral ...