Impulse noise is one of the common noise types that affect images. Median filtering
denoising method has been widely used for impulse noise. However, as the noise density …

Restricted Boltzmann machines (RBMs) are energy-based neural networks which are
commonly used as the building blocks for deep-architecture neural architectures. In this …

Traditional electronic program guides (EPGs) cannot be used to find popular TV programs. A
personalized digital video broadcasting-terrestrial (DVB-T) digital TV program …

Single-cell RNA-sequencing (scRNA-seq) is a powerful tool to quantify transcriptional states
in thousands to millions of cells. It is increasingly common for scRNA-seq data to be …

Recent advances in mobile media cloud (MMC) make it possible for users to enjoy the
multimedia applications at anytime and anywhere. Most existing scheduling algorithms for …

A successful class of image denoising methods is based on Bayesian approaches working
in wavelet representations. The performance of these methods improves when relations …

Digital TV channels require users to spend more time to choose their favorite TV programs.
Electronic Program Guides (EPG) cannot be used to find popular TV programs. Hence, this …

With the advent of Machine and Deep Learning algorithms, medical image diagnosis has a
new perception of diagnosis and clinical treatment. Regrettably, medical images are more …

This paper presents data-driven methods for echocardiogram enhancement. Existing
denoising algorithms typically rely on a single noise model, and do not generalize to the …

In recent years, cloud computing technology has matured significantly, as has the
development of digital TV services. This, therefore, has led to an increased demand for …