activity
20172020
most citedAn unsupervised bayesian approach for the joint reconstruction and classification of cutaneous reflectance confocal microscopy images

11 citations · 11 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP2020

Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution

Antonio Quintero-Rincón, Carlos D'Giano, Hadj Batatia

This paper deals with the detection of mu-suppression from electroencephalographic (EEG) signals in brain-computer interface (BCI). For this purpose, an efficient algorithm is prop…

stat.AP2019

A quadratic linear-parabolic model-based classification to detect epileptic EEG seizures

Antonio Quintero-Rincon, Carlos D'Giano, Hadj Batatia

The two-point central difference is a common algorithm in biological signal processing and is particularly useful in analyzing physiological signals. In this paper, we develop a mo…

eess.SP2019

A novel spike-and-wave automatic detection in EEG signals

Antonio Quintero-Rincón, Valeria Muro, Carlos D'Giano +2

Spike-and-wave discharge (SWD) pattern classification in electroencephalography (EEG) signals is a key problem in signal processing. It is particularly important to develop a SWD a…

stat.AP2017

Statistical modeling and classification of reflectance confocal microscopy images

Abdelghafour Halimi, Hadj Batatia, Jimmy Le Digabel +2

This paper deals with the characterization and classification of reflectance confocal microscopy images of human skin. The aim is to identify and characterize the lentigo, a phenom…

stat.ML201711 cited

An unsupervised bayesian approach for the joint reconstruction and classification of cutaneous reflectance confocal microscopy images

Abdelghafour Halimi, Hadj Batatia, Jimmy Le Digabel +2

This paper studies a new Bayesian algorithm for the joint reconstruction and classification of reflectance confocal microscopy (RCM) images, with application to the identification…