- Head: Yousri Kessentini
- Field: Pattern recognition, Computer vision, Machine learning
- Theme: Pattern recognition, Image analysis, Document processing, Deep learning, OCR, Handwriting recognition
The team is dedicated to automatically understanding multimedia data (images, video, digital documents) using deep learning techniques. We focus on acquisition, indexing, modeling, classification or automatic content recognition.
Skills: image processing (filtering, segmentation, feature extraction), machine learning and pattern recognition (connectionist, statistical and structural approaches), information fusion.
Working across disciplines of AI, Machine Learning and pattern recognition. With a team specialising in machine learning, deep learning, computer vision, data science and software, our team brings together a diverse set of skills to solve problems in these areas and build robust solutions.
KeywordsPattern recognition Computer vision Machine learning Document processing Deep learning
- ADIP: Automatic Detection of in-process pieces using robot control
- REIVE: Vehicle Identity REcognition
- TADA : Traitement Automatique de documents Arabes
- Yousri Kessentini (Assistant professor)
- Sourour Ammar (Assistant professor)
- Ilef Ben Slama (Technologue)
- Nabila Mansouri (Post-doc)
- Ahmed Chikhrouhou (PHD student)
- Marwa Dhiaf (R&D Engineer)
- Sana Khemekham (PHD student)
- Dhia Besbes (R&D Engineer)
- Mahmoud Ghorbel (PHD student)
- Tayeb Benzenati (PHD student)
- Mohamed Ali Souibgui (PHD student)
- Ines Feki (PHD student)