Prototyping a serious card game for a gamified approach to upskilling and AI integration in professional settings

In our project, we’re creating an innovative card game that blends traditional symbols, like those from tarot cards, with modern cultural references to help professionals navigate today’s complex workplace dynamics. The card game, created with different AI tools, aims to encourage strategic and speculative thinking, collaboration, and open-mindedness among employees, making room for a more […]

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Advancing Cheque Fraud Detection and Localization: A Holistic Approach Integrating CNN and Grad-CAM

The primary objective of this research is to enhance fraud detection in cheques by implementing a comprehensive approach that addresses anomalies in formatting, signatures, and other critical elements. With a focus on fortifying bank applications against financial malpractices, our goal is to develop a robust fraud localization system. To achieve this, we will utilize a […]

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Recognition of cognitive states during simulated human-vehicle interaction from EEG signals.

The project will investigate how common distractions, such as cell phone use, impact drivers’ ability to stay attentive and respond appropriately on the road. Using electroencephalography (or EEG) to monitor brain activity, we will look for patterns indicating attention or fatigue during simulated human-vehicle interaction, and classification algorithms will also be used to recognize these […]

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Ácara Climate : Mesurer les impacts financiers des changements climatiques en agriculture

Le projet consiste à développer et entraîner un modèle hybride (process-based model & computer simulation model) pour quantifier les impacts financiers des changements climatiques sur l’agriculture. Acara cherche à évoluer vers un modèle hybride intégrant des techniques de Machine Learning (ML). Cette transition marquera une étape importante avant le lancement de projets pilotes qui mettront […]

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Integrating AI with 4D Flow MRI for Advanced Cardiovascular Diagnostics

This project is dedicated to enhancing the safety and reliability of cardiovascular disease diagnosis through the innovative integration of Artificial Intelligence (AI) with 4D Flow MRI technology. By applying advanced machine learning algorithms, we aim to improve the precision and dependability of 4D Flow MRI analyses, ensuring more accurate assessments of complex heart blood flow […]

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Planification de la production hydroélectrique à court terme à l’aide de l’apprentissage par renforcement

Ce projet vise à développer différents modèles d’algorithmes d’apprentissage automatique afin de planifier la production hydroélectrique à court terme. La résolution de ce problème permet d’obtenir les débits, les volumes et les turbines en marche pour toutes les centrales d’un système de production hydroélectrique. Ayant accès à plusieurs années de données historiques, celles-ci seront exploitées […]

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Processus d’Influence de l’IA en art (PriiArt)

La diffusion à grande échelle des IA génératives (GenIA) a levé les barrières à l’entrée de l’art. Alors que certains artistes s’opposent à l’usage des GenAI en art d’autres les considèrent plutôt comme des outils permettant d’optimiser voire d’augmenter leurs capacités créatives. Ces tensions sont donc constitutives de ce qu’est le processus de création : […]

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Quantum Computing to enhance Machine Learning Accuracy

in this project, we are exploring the combination of quantum computing with machine learning to ensure a quantum-enhanced machine learning. We are focusing on the improvement of the accuracy and reliability of machine learning algorithms. While quantum improvements in supervised, unsupervised learning, and reinforcement learning have been reported, distributed models of machine learning such as […]

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The Research on the Positioning of Virtual Humans in AR Collaboration Systems

Our research expands the paradigm of 1:1 AR collaboration systems to multi-party AR collaboration systems, enabling more flexible control over the positioning of the RU. We investigate multi-party conversations involving two or more participants and one VH replacing the RU. Specifically, we vary the distance between the two LUs and the VH to examine RU’s […]

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Optimizing Optical Coherence Tomography Scanning Efficiency with Low-Rate Acquisition and AI-Based Image Synthesis

Perimeter Medical has been developing a novel optical coherent tomography (OCT) technique combined with AI to analyze tissue edges quickly. This project aims to make the method faster by acquiring images more efficiently. This will help surgeons assess tissues quicker and shorten surgery times, which in turn will lead to less time for patients to remain […]

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