This project uses the Galaxy Zoo: Hubble (or GZ:H) dataset to de-noise, reconstruct, and cluster images of galaxies using their visual features via an autoencoder and contrastive learning. The dataset ...

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 ...

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 ...

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 ...

Abstract: Convolutional neural networks have been successfully applied to hyperspectral image denoising, but they cannot effectively capture global information in the image. To address this issue, ...