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Synopsis deep learning methods have become increasingly popular for building intelligent systems. Currently, many deep learning architectures constitute the state of the art in their respective domains, such as image recognition, text generation, speech recognition, etc. The availability of mature libraries and frameworks to develop such systems is also a key factor in this success.This work explores the use of these architectures to build intelligent systems for sign languages. The creation of large sign language data corpora has made it possible to train deep learning architectures from scratch. The contributions presented in this work cover all aspects of the development of an intelligent system based on deep learning. A first contribution is the creation of a database for the Langue des Signes de Belgique Francophone (LSFB). This is derived from an existing corpus and has been adapted to the needs of deep learning methods. The possibility of using crowdsourcing methods to collect more data is also explored.The second contribution is the development or adaptation of architectures for automatic sign language recognition. The use of contrastive methods to learn better representations is explored, and the transferability of these representations to other sign languages is assessed.Finally, the last contribution is the integration of models into software for the general public. This led to a reflection on the challenges of integrating an intelligent module into the software development life cycle.Jury membersProf. Wim VANHOOF, President, University of NamurProf. Benoît FRENAY, Promoter, University of NamurProf. Anthony CLEVE, Co-promoter, University of NamurProf. Laurence MEURANT, Internal Member, University of NamurProf. Lorenzo BARALDI, External Member, University of ModenaProf. Annelies BRAFFORT, External Member, University of Paris-SaclayProf. Joni DAMBRE, External Member, University of GhentYou are cordially invited to a drink, which will follow the public defense. For a good organization, please give your answer by Friday June 6.

Professor Elio Tuci has just been awarded Research Credit funding from the FNRS. The naXys institute specializes in the analysis of complex systems, whether in astronomy and dynamic cosmology, mathematical biology, optimization in optics, economic complexity or the study of the stability and robustness of these systems. The institute is structured around 6 research axes: Space, Bio, Optics, Eco, Robust and Robotics.

The workshop will feature:A keynote presentation on public value and AI implementation at VRT.Sessions on discoverability, user agency, and explainability.Discussions on regulation, including perspectives on the AI Act and transparency in media.An interactive session showingcasing AI-driven prototypes.The event will also highlight our project's latest findings. Join us for a day of thought-provoking discussions, knowledge exchange, and networking opportunities!Would you like to attend? Places are limited and will be allocated on a first-come, first-served basis, so register as soon as possible. Registration will close on April 11, 2025. More information here

For Bruno Dumas, computer science fits in with the principles of applied psychology Artificial intelligence (AI) is interfering in our professional as well as our private lives. It both seduces and worries us. On a global scale, it is at the heart of major strategic, societal or economic issues, still being debated in mid-February 2025, at the AI World Summit in Paris. But how can we, as users, avoid being subjected to it? How can we gain access to the necessary transparency of its workings? By placing his research prism on the user's side, Bruno Dumas is something of a "computer psychologist". An expert in human-computer interaction, co-president of the NaDI Institute (Namur Digital Institute), he defends the idea of a reasoned and enlightened use of emerging technologies.

Can a computer learn a language like a child? A recent study published in the leading journal Computational Linguistics by Professors Katrien Beuls (Université de Namur) and Paul Van Eecke (AI-lab, Vrije Universiteit Brussel) sheds new light on this question. The researchers argue for a fundamental revision of the way artificial intelligence acquires and processes language.

This thesis presents a novel approach to address the challenges of deploying and managing Network Functions Virtualization (NFV) in resource-constrained and multi-domain environments. The proposed solution leverages a Raspberry Pi clusterbased approach for NFV deployment in resource-constrained environments, combined with a deployable Sidecar VNF (S-VNF) coordinator for multi-domain NFV orchestration.The thesis demonstrates the feasibility of integrating NFV into edge computing environments by successfully deploying and managing Network Services (NSs) on a Raspberry Pi cluster. The S-VNF coordinator facilitates efficient cross-cloud NFV deployment and management while ensuring security and interoperability.While the obtained deployment and scaling delays in the testbed setup were significant due to the bare-metal deployment process used, the proposed solution remains valuable in environments where service maintenance time is a critical factor.By automating deployment and scaling, organizations can minimize the impact of service maintenance time, improve customer satisfaction, and enhance system resilience. Moreover, the solution enables NFV to be deployed effectively in edge environments, providing benefits such as reduced latency and improved network performance.Overall, this thesis contributes to the advancement of NFV by providing innovative solutions for deployment and management in challenging environments. The proposed framework has the potential to enable the widespread adoption of NFV and drive the development of new network services.Directed by Prof. Laurent SCHUMACHER and Prof. Sokchenda SRENG.In front of a jury composed of:Prof. Wim VANHOOF, President, University of NamurProf. Laurent SCHUMACHER, Co-Promoter, University of NamurProf. Sokchenda SRENG, Co-Promoter, ITC Graduate School (Cambodia)Prof. Florentin ROCHET, Internal Member, University of NamurProf. Johann MARQUEZ-BARJA, External Member, University of AntwerpProf. Bruno QUOITIN, External Member, University of MonsProf. Raveth HIN, External Member, ITC Graduate School (Cambodia)You are cordially invited to a drink, which will follow the public defense.For good organization, please give your answer by Thursday March 20 by means of this link.Contact: Daelman Isabelle - isabelle.daelman@unamur.be

Instantly obtain a translation in sign language (LSFB) of a word written in French: that's what MOSI (Du mot au signe) makes possible. This new tool is the fruit of a collaboration between the University of Namur, the asbl École et Surdité and the asbl LSFB, supported by the King Baudouin Foundation.

Critical thinking, the art of productive doubt, can be learned and cultivated. Faced with information overload and the spread of artificial intelligence, it is more important than ever for students to develop this skill throughout their studies. At UNamur, this educational necessity takes many forms.