Traitement d'images numériques.
Modélisation et simulation.
Pr. MOKHATI Farid.
Dr. BOUROUIS Abdelhabib.
Dr. TENACHI Abd-Ed-Daîm.
Le laboratoire de recherche sur les systèmes informatiques complexes ReLa(CS)² de l’université d’Oum El Bouaghi, organise le Mardi 11 et Mercredi 12 Décembre 2018 les premières "Journées d'étude sur L’Intelligence Artificielle et ses Applications" à l’auditorium de l’université d’Oum El Bouaghi.
L’intelligence artificielle est un des grands enjeux du siècle. Elle est utilisée dans de nombreux domaines de l’Informatique tels que le traitement d’image, la vision artificielle et les systèmes embarqués. Depuis la dernière décennie, l’intelligence artificielle connaît une véritable explosion tant sur le plan académique qu’industriel, avec le développement du big data, de la data science et du deep learning.
Ces deux journées ont pour objectif de promouvoir les échanges et la coopération des chercheurs dans le domaine de l’intelligence artificielle et leur permettre de se rencontrer, de présenter leurs travaux de recherche en cours, de partager leurs expériences, et de discuter leurs idées avec des intervenants de renom qui sont mieux expérimentés.
Ces journées s’adressent à tous les chercheurs du laboratoire et du département de mathématiques et d’Informatique (enseignants et doctorants) et visent à présenter des communications orales. Trois conférences plénières sont également prévues.
Le programme détaillé des journées ; (Télécharger)
Dernière Mise à jour le: 21/04/2019.
Galerie de photos:
Professor, University of Oulu, Finland, Senior Member of IEEE
Recipient of the 100-Talent Program (Visiting Professor) of Shaanxi Province, China
Jan Koenderink Prize for fundamental contributions in computer vision
BTAS 2016 Five Year Highest Impact Award
Chairman of the Pattern Recognition Society of Finland (2017-2018)
Google Scholar: https://scholar.google.com/citations?user=heC40hcAAAAJ&hl=en
From Biometrics to Medical Diagnosis using Handcrafted Features and Deep Learning
During the past decade, there have been numerous research and development efforts in the field of wearable health monitoring systems that were motivated by the need to monitor a person's health status outside of the hospital. However, most current techniques typically require users to strap on bulky sensors, chest straps or sticky electrodes. This obviously discourages regular use because the sensors can be uncomfortable or encumbering. Hence, in order to make health monitoring part of the fabric of everyday life, there is a need for revolutionary technologies that are comfortable (e.g. non-invasive and contact free), simple to use and unobtrusive. This presentation discusses some recent advances in using computer vision and artificial intelligence for designing futuristic unobtrusive technologies for health diagnosis and monitoring that people can effortlessly use in their daily lives without any contact. In terms of image features and representations, the current tendency is toward using automatically learned features e.g. using deep learning instead of using hand-crafted features. This talk will be an opportunity for brainstorming around some recent advances in biometrics and medical diagnosis using handcrafted features and deep learning.
Abdenour Hadid received his Doctor of Science in Technology degree in electrical and information engineering from the University of Oulu, Finland, in 2005. Now, he is an Associate Professor at Center for Machine Vision and Signal Analysis, University of Oulu, Finland. His research interests include biometrics and facial image analysis, machine learning, human-machine interaction, personalized healthcare and mobile applications. He has authored more than 160 papers in international conferences and journals, and served as a reviewer for many international conferences and journals. His research works have been well referenced by the research community with more than 12000 citations so far according to Google Scholar. Among his significant scientific achievements is the methodology for face detection and recognition using Local Binary Patterns (LBP) which has evolved to present a major breakthrough in face analysis. The proposed approach has been adopted by many leading scientists and research groups around the world. Jan Koenderink Prize for fundamental contributions in computer vision has also been received. Prof. Hadid participated and played a key role in different European projects. One of these projects (http://www.tabularasa-euproject.org/) has been selected as a Success Story by the European Commission. His achievements have been recognized by many other awards and grants including the highly competitive Academy Research Fellow position from the Academy of Finland during 2013-2018, and a very prestigious international award within the 100-Talent Program (Outstanding Visiting Professor) of Shaanxi Province, China. These achievements would not have been possible without his rich international network of collaborators in France, Algeria, Spain, Italy, Japan, China, Japan, Canada, USA, Switzerland and UK. Prof. Hadid was the Chairman of the Pattern Recognition Society of Finland (2017-2018) and is currently a senior member of IEEE.
Abbas Cheddad (PhD, SMIEEE)
Associate Professor (Docent) in Computer Science
Department of Computer Science and Engineering
Blekinge Institute of Technology.
SE-371 79, Karlskrona, Sweden.
Office: +46 4 55-385863
Email: abbas.cheddad [AT] bth.se
Work Profile: https://www.bth.se/staff/abbas-cheddad-abc
Image Processing in Data Science: Current prospects and future challenges
This era is believed to be the golden age for computer visionand its core components, namely, image processing and pattern recognition. Research breakthroughs are no longer constrained within the lab environment. Image processing, in particular, now plays a vital role in many advances benefiting society in data science, such as autonomous vehicles and robotics, biometric security and surveillance, optical character recognition and document retrieval,satellite technology, medical imaging, etc. The current prosper of image processing field could be partially attributed to the advances in machine/deep learning.The latter has been demonstrated in many applications such as image classification, detection and processing. In this talk I will present some of the key image processingresearch areaswhich we are involved in together with the industry in Sweden. The talk will also bring about some open research problems.
Abbas Cheddad is a senior IEEE member and is currently an Associate Professor at the Blekinge Institute of Technology (BTH) in Sweden. He received his PhD, with distinction, from the University of Ulster, UK, in 2010. Cheddad is leading aresearch group on big data analytics for image processing. Currently, the group is collaborating, research-wise, with some companies, SONY Mobile (Lund), Arkiv Digital AB (Mariestad, Sweden) and GKN Aerospace Sweden AB, by addressing practical industrial problems. Prior to joining BTH,Dr. Cheddad held research positions at several Universities in Sweden, namely, Umeå University and Karolinska Institute where he focused his research on medical image analysis. Dr. Cheddad received several awards including the 25K Award for New Entrepreneurs in the Hi-Tech category sponsored by Northern Ireland Science Park (NISP) and is a co-founder of a spin-off UK-based company. He was the chair in 3 international conferences/workshops, a PC member in dozens of conferences and has been invited for talks at several venues. He has in records, 1 book, 1 book chapter (invited), 2 granted patents and more than fifty journal and conference papers.
Doctor Professor in Computer Science
Department of Math and Computer Science
Larbi Ben M’hidi university of Oum El-Bouaghi
Email: b.nini [AT] univ-oeb.dz, brahim_nini [AT] yahoo.fr
Web page: http://www.univ-oeb.dz/relacs/nini.html
Image Processing… What is it, How and Why?
Image processing field becomes larger and larger with the latest advances in technologies. Just some decades ago, it was possible for someone to cover most of related concepts. Nowadays, it becomes difficult to a single person to master all the domains. All researchers are becoming specialized in very narrow axes. Even users, the apps are becoming sophisticated at the point they require to be trained before using them. So, synthesising image processing basics to understand what happens in the underneath of the different applications and in research works is important for a beginner and would be a nice recall for a professional. This is what is intended throughout the slides of the presentation. They start from scratch, and build the necessary knowledge by explaining what is an image, what can we do with and what supports the process. Then, they explain how is it done. Finally, they highlight the importance of image processing and its need for nowadays and the future.
Brahim Nini is currently a researcher-teacher at the university of Oum El-Bouaghi. He received his PhD from the University of AbdelhamidMehri (Constantine 2) in 2008. He was awarded with a habilitation degree to direct scientific researches in 2013. In 2017, he obtained the rank of professor. Currently, Nini leads a group of doctoral researchers as a team in the ReLa(CS)² laboratory in the same university. His research works are mainly oriented towards image processing. He works on image indexing, augmented reality, human body gestures analysis, and image security. He has several journal and conference papers, and two manuscripts. He is a member of the National Educational Committee of Computer Science Domain where he participates in the establishment of the national curricula.