Hacheme AYASSO
Maître de conférences UGA
Equipe Communication and Information in Complex Systems
Département Images et Signal
ME CONTACTER / CONTACT ME
Mail : hacheme.ayasso@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1197
Tél.33 (0)4 76 82 71 04
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Nonlinear microwave imaging for breast-cancer using a variational Bayesian algorithm

Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Nonlinear microwave imaging for breast-cancer using a variational Bayesian algorithm. SIAM Conference on the Life Sciences, Jul 2016, Boston, United States. pp.PP1, 〈http://www.siam.org/meetings/ls16/〉. 〈hal-01459711〉

SELFI: an object-based, Bayesian method for faint emission line source detection in MUSE deep field data cubes

Céline Meillier, Florent Chatelain, Olivier Michel, Roland Bacon, Laure Piqueras, et al.. SELFI: an object-based, Bayesian method for faint emission line source detection in MUSE deep field data cubes. Astronomy and Astrophysics - A&A, EDP Sciences, 2016, 588, pp.A140. 〈10.1051/0004-6361/201527724〉. 〈hal-01322356〉

Contrôle des erreurs pour la détection d'événements rares et faibles dans des champs de données massifs

Céline Meillier, Florent Chatelain, Olivier Michel, Hacheme Ayasso. Contrôle des erreurs pour la détection d'événements rares et faibles dans des champs de données massifs. XXVème colloque GRETSI (GRETSI 2015), Sep 2015, Lyon, France. 〈hal-01198721〉

Error control for the detection of rare and weak signatures in massive data

Céline Meillier, Florent Chatelain, Olivier Michel, Hacheme Ayasso. Error control for the detection of rare and weak signatures in massive data. 23rd European Signal Processing Conference (EUSIPCO-2015), Aug 2015, Nice, France. 2015. 〈hal-01198717〉

MCMC and variational approaches for Bayesian inversion in diffraction imaging

Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. MCMC and variational approaches for Bayesian inversion in diffraction imaging . J.-F. Giovannelli, J. Idier. Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing, Wiley-ISTE, pp.201-224, 2015, Digital signal and image processing series, 978-1-84821-637-2. 〈hal-01262038〉

Nonparametric Bayesian extraction of object configurations in massive data

Céline Meillier, Florent Chatelain, Olivier Michel, Hacheme Ayasso. Nonparametric Bayesian extraction of object configurations in massive data. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2015, 63 (8), pp.1911-1924. 〈10.1109/TSP.2015.2403268〉. 〈hal-01129038〉

A Gauss-Markov mixture prior model for a variational Bayesian approach to microwave breast imaging

Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. A Gauss-Markov mixture prior model for a variational Bayesian approach to microwave breast imaging. CAMA 2014, Nov 2014, Juan-les-Pins, France. Proceedings of the IEEE International Conference on Antenna Measurements and Applications, pp.ID SP13.4, 2014. 〈hal-01103674〉

Inverse scattering in a Bayesian framework: application to microwave imaging for breast cancer detection

Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Inverse scattering in a Bayesian framework: application to microwave imaging for breast cancer detection. Inverse Problems, IOP Publishing, 2014, 30 (11), pp.114011. 〈http://iopscience.iop.org/0266-5611/30/11/114011/pdf/0266-5611_30_11_114011.pdf〉. 〈10.1088/0266-5611/30/11/114011〉. 〈hal-01103456〉

A gradient-like variational Bayesian approach: Application to microwave imaging for breast tumor detection

Leila Gharsalli, Bernard Duchêne, Ali Mohammad-Djafari, Hacheme Ayasso. A gradient-like variational Bayesian approach: Application to microwave imaging for breast tumor detection. 21st IEEE International Conference on Image Processing (ICIP 2014), Oct 2014, Paris, France. pp.1708-1712 2014, Processing of the Image Processing (ICIP 2014). 〈10.1109/ICIP.2014.7025342〉. 〈hal-01266174〉

Optical imaging in a variational Bayesian framework

S. Arhab, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Optical imaging in a variational Bayesian framework. Journal of Physics: Conference Series, IOP Publishing, 2014, 542, pp.012008. 〈http://iopscience.iop.org/1742-6596/542/1/012008/pdf/1742-6596_542_1_012008.pdf〉. 〈10.1088/1742-6596/542/1/012008〉. 〈hal-01103469〉

ENCADREMENT DE THESES / PhD THESIS SUPERVISED
Prénom NOM Date d'entrée en thèse Sujet Ecole doctorale
COTTE Florian01/03/2016Estimation d’objets de très faible amplitude dans des images radiologiques X fortement bruitéesEEATS

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal