Professeur, Equipe ImapAdresse électronique : denis.hamad [at] lisic.univ-littoral.fr
Téléphone : +33 (0)3 21 46 56 60
Fax : +33 (0)3 21 46 55 75
Adresse : 50 reu F. Buisson, BP 719, 62228 Calais Cedex
Denis Hamad is professor at the University of Littoral Côte d’Opale since 2002. He obtained a HDR (Habilitation à Diriger la Recherche) degree in neural networks for unsupervised pattern classification and a Ph.D. degree in detection and validation of measurements in complex systems from the University of Lille 1 Sciences and Technologies-France in 1997 resp. in 1986.
Between 1998 and 2002, he was Professor at University of Picardie Jules Vernes, Amiens-France and Head of the CREA Laboratory. His main research interests are in: Machines learning, unsupervised classification, image and signal segmentation.
Since 1993, he has been involved in many industrial projects related to machine learning systems: Glass bottles inspection, wind turbine supervision, robot control, fault detection and diagnosis systems, transport security and more recently monitoring of marine environment ecosystem.
Actually, his research is in the area of signal processing and machine learning for "environment, coastal environment, and sustainable development”. He is involved in the Interreg 2 Seas DYMAPHY Project “Development of a DYnamic observation system for the assessment of MArine water quality, based on PHYtoplankton analysis”. He managed the PhytoClas project which has been selected as innovative project and supported by the university ULCO. PhytoClas has the objective of characterization and classification of phytoplankton by Cytometry signal analysis and image processing. He managed the CLASPEC project “Spectral Clustering for Color Image Segmentation and Audio Signals”. CLASPEC has been supported by “Graisyhm research federation”. He managing the REPAR project “Représentation Parcimonieuse et Apprentissage Dynamique pour le signal et l'image”. REPAR 2014-2017, is supported by AIRR Regional found.
LBP histogram selection based on sparse representation for color texture classificationV. TRUONG HOANG, A. POREBSKI, N. VANDENBROUCKE, D. HAMAD
International Conference on Computer Vision Theory and Applications (VISAPP'17), 27 February - 1 March, 2017, Porto, Portugal
Automatic clustering for of MRI images, application on perfusion MRI of brain.P. Chuzel, A. Mansour, J. Ognard, J. Gentric, D. Hamad, N. Betrouni, and L. Bressollette
In the 2nd International Conference on Frontiers of Signal Processing (ICFSP 2016), Warsaw, Poland, October 15-17, 2016.
LBP parameter tuning for texture analysis of lace imagesV. TRUONG HOANG, A. POREBSKI, N. VANDENBROUCKE, D. HAMAD
Second International Conference on Image Processing and Applications (IEEE-IPAS'16), November 5-7, 2016, Hammamet, Tunisia
Selection of Income Indicators for Middle East Country ClassificationKalakech A., Kalakech M., Hamad D.
Accepted in Int. Conf. on Digital Information Processing and Communications Faculty of Engineering - Lebanese University, Lebanon, April 21-23, 2016.
Perception of noise in Global Illumination based on Inductive LearningJoseph Constantin, Ibtissam Constantin, André Bigand, Denis Hamad
IEEE World Congress on Computational Intelligence, IJCNN, Vancouver Canada, 24-29 July 2016.
Selection of World Development Indicators for Countries Classification.Mariam Kalakech, Ali Kalakech and Denis Hamad
The first International Conference on Digital Economy (ICDEc2016), Carthage, Tunisia, April 28-30, 2016.
Image Noise Detection in Global Illumination Methods based on FRVMJoseph Constantin, André Bigand, Ibtissam Constantin, Denis Hamad
Neurocomputing journal. doi:10.1016/j.neucom.2014.10.090
Constrained graph embeddingDenis Hamad
Invited speak in International Symposium on 3D Imaging, Metrology, and Data Security, September 26th - 29th, 2015, Shenzhen, China.
Modèle de Markov Caché hybridé pour la surveillance de l’environnement marin.Kévin Rousseeuw, Émilie Caillault, Alain Lefebvre, Denis Hamad
Chapitre d'ouvrage. EditionsCNRS, à paraître.
A fast embedded selection approach for color texture classification using degraded LBPPOREBSKI A., VANDENBROUCKE N., HAMAD D.
5th International Conference on Image Processing Theory, Tools and Applications (IEEE-IPTA'15), pp. 254-259, Orléans (France), November 2015.
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