ALADINE CHETOUANI

Associtate Professor (HDR)

PRISME Laboratory

Polytech'Orleans, University of Orleans

Orleans, France

firstname.lastname(at)univ-orleans.fr

Aladine Chetouani on: ResearchGate, dblp, Google Scholar

Aladine Chetouani is an IEEE senior member. He received his master’s degree in computer science from the University Pierre and Marie Curie, France, in 2005, and his Ph.D. degree in image processing from the University of Paris 13, France, in 2010. From 2010 to 2011, he was a postdoctoral researcher with the L2TI Laboratory, Paris 13 University. In 2020, he benefited from a CNRS delegation year at the L2S laboratory, Centrale Supélec, Université Paris Saclay, France. He is currently an associate professor with the Laboratory PRISME, Orleans, France. He also received the Habilitation degree entitled “On the use of visual attention and deep learning for blind quality assessment of multimedia contents” from Université d'Orléans in 2020. He led and participated in several research projects. He supervised more than 20 students (Ph.D. and Master). He serves as a reviewer for major conferences and journals in the field of image analysis and pattern recognition. He co-edited different special issues in international journals (IEEE JSTSP, MTAP and so forth) and organized different special sessions in international conferences (IEEE ICIP, IEEE ICME, EURASIP EUVIP, etc.). He is co-author of more than 120 research publications in international refereed journals and conference proceedings. He served in several program committees. He is an elected member of IEEE SPS MMSP, IEEE SPS IVMSP and IEEE SPS CDC technical committees. He is one of the co-chairs of the CSP-SSD22. He is/has been the general chair of CBMI23, CBMI24 and IEEE IPTA24. He is one of the TPC chair of EUVIP24. He is an associate editor at IEEE TCSVT and IEEE TMM. His present interests are in perceptual analysis of multimedia content for multimedia contents (2D, stereo, 3D, etc.) using and developing deep learning models. Sevral applications: objet detection, visual attention prediction, classification of medical images, features representation analysis, etc.