We propose a semi-automated brain lesions segmentation method utilizing deep learning techniques and point prompting such as foundation models (SAM). This developed approach aims to assist physicians in the follow-up of multiple sclerosis disease at different stages, enhancing the likelihood of successful treatment for patients. The key contribution of this research lies in the advancement […]

Caveolin-1 (CAV1) is a protein on the plasma membrane that forms cup-shaped structures caveolae, which flatten to protect cells under mechanical stress. However, the relationship between the caveolae and other CAV1 structures, scaffolds and dolines, in the process of caveolae formation and flattening is unclear. A challenge is to differentiate caveolae from scaffolds using conventional […]

Quantum information metrics including fidelity, quantum divergences, and the trace norm provide the mathematical foundation for studying and understanding quantum states and processes. As such, quantum information metrics play a crucial role in quantum computing, simulation of quantum systems, and quantum machine learning (including quantum clustering, generative models, and machine learning of, and by, quantum […]

Le projet de stage chez Empenn a pour objectif de modéliser les conséquences des traumatismes crâniens chez les enfants en se basant sur des données d’imagerie par résonance magnétique (IRM). Ce stage sera mené par la stagiaire Andjela Dimitrijevic, se concentrant principalement sur l’acquisition de données liées au traumatisme crânien léger (TCC) chez les enfants, […]

The main objective of the current research is to enhance the detection, clustering, and estimation of Extreme Precipitation Events (EPEs) in arid and semi-arid regions. To achieve this goal, we propose a novel framework called Machine-learning-based Clustering-merging algorithms (ML-CMAs) for satellite-based precipitation products (SPPs). Daily precipitation measurements were utilized for training and evaluating EPEs estimation […]

This project addresses a flexible autonomous robotic welding system. Despite the advancements in robotic systems, there are still significant challenges in developing welding robots for industrial applications. Challenges such as accurately determining the weld seam coordinates, ensuring the electrode head remains at the correct distance from the weld seam, and mitigating high environmental noise have […]

This project addresses a flexible autonomous robotic welding system. Despite the advancements in robotic systems, there are still significant challenges in developing welding robots for industrial applications. Challenges such as accurately determining the weld seam coordinates, ensuring the electrode head remains at the correct distance from the weld seam, and mitigating high environmental noise have […]

The Actively Sober app is an ambitious project that combines advanced artificial intelligence with a keen understanding of cultural nuances to address the widespread issue of alcohol misuse. By employing AI algorithms that continuously scan digital platforms to identify and block alcohol-related content, the app aims to create a supportive environment for users, helping them […]

The ordered median is an important class of facility location problem that encompasses multiple other relevant location problems as particular cases. Deepening our understanding of this problem, its mathematical properties and proposing novel methodological contributions for its solution lies at the core of this project. We will consider a recent algorithm for this problem developed […]

L’estimation des forts débits dans un contexte de changement climatique est une tâche essentielle à bien des égards pour notre société. Elle permet en l’occurrence d’analyser l’impact et les stratégies de mitigation face aux aléas naturels comme les inondations. Différentes approches ont été proposées pour répondre à ce besoin dont la modélisation hydro-climatologique (MHC) et […]

This project aims to employ cutting-edge deep learning models to address the critical issue of water leakage in water distribution networks (WDNs). Leakage in WDNs leads to significant water wastage, infrastructure damage, service disruption, and even contamination. The proposed approach leverages Convolutional Neural Networks (CNNs) trained explicitly for optimizing leak detection. Using synthetic datasets that […]

We proposed a breath analyzer to identify viruses by utilizing an affordable fiber coupler. This sensor captures the optical absorbance spectrum, which contains the unique signatures of viruses present in the breath. The device is user-friendly: simply exhale into the analyzer to receive results. Our product addresses the traditional challenges of virus detection, eliminating high […]