Profile Yousri Kessentini

First Name
Yousri

Last Name
Kessentini

Address
Technopole of Sfax, PO Box 275, Sakiet Ezzit, 3021 Sfax - Tunisia

Zip code
3038

Biography
Yousri KESSENTINI is Associate Professor at the Digital Research Center of Sfax (CRNS) and the head of the DeepVision research team. He received his Ph.D. degree in the field of pattern recognition from the University of Rouen, France in 2009. He was postdoctoral researcher at ITESOFT company and LITIS laboratory from 2011 to 2013. He is certified as an official instructor and ambassador from the NVIDIA Deep Learning Institute. His main research areas concern deep learning, document processing and recognition, data fusion, and computer vision. He has participated in several research projects and technology transfer projects. He has published more than 60 papers in international conferences and journals. He is also a reviewer for several international conferences and journals in the field of pattern recognition and computer vision.
Scientific publications
Title Cited by Year
ST-KeyS: Self-supervised Transformer for Keyword Spotting in historical handwritten documents
SK Jemni, S Ammar, MA Souibgui, Y Kessentini, A Cheddad
Pattern Recognition 170, 112036, 2026

16 2026
ORCA: Orchestrated Reasoning with Collaborative Agents for Document Visual Question Answering
A Lassoued, MA Souibgui, Y Kessentini
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2026

3 2026
Hierarchical Behavioral Transformer Modeling and Multimodal Context Fusion for Student Engagement Detection
A Boubaker, S Bettoumi, L Prevost, M Ben Hajhmida, Y Kessentini
Proceedings of the 28th International Conference On Multimodal Interaction …, 2026

1 2026
Recognition-aware diffusion models for handwritten document enhancement
SK Jemni, H Aloui, S Ammar, Y Kessentini
Multimedia Tools and Applications 85 (8), 682, 2026

0 2026
PIQA-Tr: a transformer-based model for no-reference pan-sharpened image quality assessment
R Hentati, S Ammar, Y Kessentini, A Kallel
Journal of Applied Remote Sensing 20 (3), 035501-035501, 2026

0 2026