Blind and universal image denoising consists of using a unique model that denoises images with any level of noise. It is especially practical as noise levels do not need to be known when the model is developed or at test time. We propose a theoretically-gr ...
Removal of noise from fluorescence microscopy images is an important first step in many biological analysis pipelines. Current state-of-the-art supervised methods employ convolutional neural networks that are trained with clean (ground-truth) images. Recen ...
The low-light performance of a CMOS image sensor (CIS) is one of the most important performance metrics in a camera, whether it is used in products for consumer electronics or in an image-acquisition system for machine vision or the Internet-of-Things (IoT ...
Noise analysis applied to nuclear reactor physics is a powerful tool to investigate a reactor's kinetic parameters, and more generally underlying physical processes determining core behavior. The kinetic parameters are the coefficients of simplified time-d ...
The collective behaviour of stochastic multi-agents swarms driven by Gaussian and non-Gaussian environments is analytically discussed in a mean-field approach. We first exogenously implement long range mutual interactions rules with strengths that are weig ...
In this work, we present a novel technique to locate partial discharge (PD) sources based on the concept of time reversal. The localization of the PD sources is of interest for numerous applications, including the monitoring of power transformers, Gas Insu ...
Objective. Among the different approaches for denoising neural signals, wavelet-based methods are widely used due to their ability to reduce in-band noise. All wavelet denoising algorithms have a common structure, but their effectiveness strongly depends o ...
The transverse emittance growth rate of colliding hadron beams driven by external sources of noise is investigated based on existing analytical model as well as on macro-particle simulations and comparison to experimental data at the Large Hadron Collider ...
Nowadays, efficient and remote health monitoring is becoming increasingly important, given both the ageing of population and the combined action of an increase in obesity level and cardiovascular diseases. The healthcare industry is becoming more reliant o ...
