Évènements / S3

S3 Seminar
Évènements à venir

Vascular networks, from low-level vision to generative models

Speaker — Hugues Talbot (CVN, CentraleSupélec, INRIA, Université Paris-Saclay) Abstract — The study of vascular networks is important in medicalimaging because disease affecting blood vessels is the first cause ofmortality and morbidity in the Western world. Yet, surprisingly, theses studies have not been the subject of majorresearch efforts. From the low-level vision point of view, […]

27/11/2019

Computational characterization of supra-threshold hearing to understand speech-in-noise intelligibility deficits

Speaker — Emmanuel Ponsot (Laboratoire des Systèmes Perceptifs, ENS) Abstract — A largely unresolved problem in hearing sciences concerns the large heterogeneity observed among individuals with similar audiograms (hearing thresholds measured in quiet) in understanding speech in noisy environments. Recent studies suggest that supra-threshold auditory mechanisms (i.e. that operate above detection threshold) play a prominent […]

20/11/2019

Test d’hypothèses bayésien non paramétrique et application à la modélisation de la zone du langage

Speaker — Diarra Fall (Institut Denis Poisson, UMR CNRS, Université d’Orléans et de Tours) Abstract — Dans cet exposé, je parlerai de modèles bayésiens non paramétriques et de tests d’hypothèses, avec pour exemple d’application, un travail en cours avec le centre hospitalier régional d’Orléans portant sur l’estimation de la zone contrôlant le langage chez des […]

18/10/2019

Safe squeezing for antisparse coding

Speaker — Clément Elvira (PANAMA research group, Iniria, CNRS, IRISA – Rennes) Abstract — Spreading the information over all coefficients of a representation is a desirableproperty in many applications such as digital communication or machine learning. Thisso-called antisparse representation can be obtained by solving a convex program involving a$\ell_\infty$-norm penalty combined with a quadratic discrepancy. […]

04/10/2019

A Bayesian deep learning approach in thermal remote imaging with hyper-resolution

Speaker — Ning Chu (Institute of process equipment, College of Energy Engineering, Zhejiang University (Hangzhou, China)) Abstract — Remote monitoring and early warning of thermal source abnormality play more and more important roles in fire prevention for the museums and historical monuments (Notre dame de Paris e.g.), metro and electric vehicle (Tesla e.g.) etc. However, […]

09/07/2019