SIIM : SIgnal-Image-Modeling

Keys Words

Modeling, ill-posed inverse problems (blind sources separation – unmixing – multidimensional deconvolution (MIMO systems)), dimension reduction, estimation, (heterogeneous) data fusion, supervised/unsupervised learning, classification, survey/decision, (Convolutive) Neural Networks, Deep Learning, matrix and tensor decompositions, stochastic and deterministic optimization, non-stationary processes (time-frequency (spatial) distributions, adaptive algorithms), linear and multilinear algebra, low rank approximation, approximation theory, nonlinear and chaotic dynamical system theory.






BOUCHARA Frederic  Enseignant-Chercheur / Chercheur
BOUCHOUICHA Moez  Enseignant-Chercheur / Chercheur
CHAMBARET Guillaume  Doctorant
ELQUATE Karima  Doctorant
ENEL Laurent  Enseignant-Chercheur / Chercheur
FRIZZI Sebastien  Doctorant
GUIS Vincente  Post-Docs / ATER / Ingenieurs
LAMOURET Marie  Doctorant
LUCIANI Xavier  Enseignant-Chercheur / Chercheur
MAIRE Sylvain  Enseignant-Chercheur / Chercheur
MINGHELLI-ROMAN Audrey  Enseignant-Chercheur / Chercheur
MOREAU Eric  Enseignant-Chercheur / Chercheur
NGUYEN Thanh Phuong  Enseignant-Chercheur / Chercheur
NGUYEN Thanh Tuan  Doctorant
NGUYEN Thi Hong Hiep  Post-Docs / ATER / Ingenieurs
PRISSETTE Cyril  Enseignant-Chercheur / Chercheur
SANCHEZ Guillaume  Doctorant
SOUQUIERES Laura  Doctorant
THIRION-MOREAU Nadege  Enseignant-Chercheur / Chercheur
VADAKKE-CHANAT Sayoob  Post-Docs / ATER / Ingenieurs

Research interests

The Project Team « SIgnal-Image-Modeling’’ (SIIM) is part of the Signal & Image pole of the LIS laboratory. This team is hosted in the SeaTech engineering school of the University of Toulon (La Garde site).

The researches of the members of the SIIM team are gearing towards data sciences & analysis, and concern more precisely: signal and image processing, computer vision, machine learning and optimization.

They range from the observation or the physical study of the data for modeling or characterization purposes or their processing and analysis. The main aims are to retrieve meaningful information or latent variables, to help the end-users with the interpretation of the results or to develop automatic decision or diagnostic assistance systems. This involves the development of innovative theoretical approaches and the effective implementation of these methods through numerical computation and high performance algorithms. These (dedicated) solutions also have to be able to take into account the specificities and constraints linked to the considered application. Depending on it, we can handle different kind of datasets: multidimensional or multimodal signals, multi- or hyper- spectral images, 3D or 4D fluorescence spectroscopy imaging, video sequences, etc.


Main Lines

Signal Processing – Image processing – Computer Vision – Machine learning


Main Fields of application

Environmental data observation or monitoring, environmental data analysis/mining, marine surveillance, written document analysis, biomedical engineering, diagnostic assistance


Local ecosystem and valorization

MEDD and INPS poles of the Toulon University, IRSN, IFREMER, CNES, Mediterranean Sea Cluster (pôle MER méditerranée), Booster Space4Earth/SafeCluster, French customs, Airbus Defense and Space, CS Technologies, Thales Alenia Space, Naval Group, Sofresud, Hexaglobe, Seaviews, TVT Innovation


Scientific publications