Advancing traceability in informal supply chains through applied AI and ML

PemPem develops tools to ensure product traceability in informal supply chains using AI. These informal supply chains employ over 60% of the working population worldwide. They typically have highly inefficient operations due to very limited access to information and a reliance on opaque word-of-mouth coordination. While PemPem has started solving the problem of collecting data […]

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Contextual portrait detection

A frequently occurring problem in face verification in Jumio is that stock face detectors find multiple faces in the input image. The decision which one should be selected for the face verification step is not clear. Common reasons being, users submitting a single image with both selfie and document id. There can be other people, […]

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Organisation du travail dans les services préhospitaliers d’urgence : facteurs facilitant le déploiement du travail et le maintien au travail des paramédics lors d’une pandémie (COVID19)

Le projet présenté porte sur l’organisation du travail dans les services d’urgence et vise à faire ressortir les facteurs facilitant le déploiement du travail et le maintien au travail des paramédics lors d’une pandémie. Actuellement, les services ambulanciers d’urgence font face à des défis importants afin de s’assurer que la sécurité de la population de […]

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Le musée face aux enjeux d’une expographie et médiation numériques participatives : l’exemple de la plateforme éducative educart.ca du MBAM et son évolution en dispositif de réalité virtuelle

Soyez au coeur de l’expérience muséale! L’Application ÉducArt en VR invite l’usager à découvrir de manière innovante toute une série d’objets et d’oeuvres d’art de collection issus du Musée des Beaux-Arts de Montréal, et à participer, en collaboration avec le musée, à la construction de cette exposition virtuelle. Cette “réappropriation patrimoniale” et gamification de la […]

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New designs for Bayesian adaptive cluster randomized trials for an individualized clinical support tool with capacity to support distance follow up and treatment of depression

Depression is a common and often devastating illness that contributes to suffering for patients and families and is also the number one cause of disability globally. Many patients do not respond to their first trial of treatment, and managing depression according to best practices can be difficult for clinicians. Using the power of machine learning, […]

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Scene Graph Image Interpretation Tools

In this project we will look at tools to represent the content of an image and the relationships between its salient objects. The purpose of these tools is not only to enumerate the object represented in an image and identify their surroundings but also to describe how these entities are interacting with each other. We […]

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An ultra-small vital sign monitoring multi-sensing platform

This collaborative research project between iMD research and prof. Benoit Gosselin aims to design and test an tiny, inexpensive and easy-to-use wearable multi-sensing platform to continuously monitor patients remotely, and help greatly to manage COVID-19. The envisioned platform will use CMOS custom integrated circuits and advanced packaging technology to achieve an extreme level of miniaturization. […]

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Using semi-supervised learning for classification of sport images

Artificial intelligence (AI) is rapidly becoming one of the most critical aspects in both business and science, and an increasing number of leading technology companies in Canada are at the forefront of AI development and innovation. The proposed research project aims at developing AI algorithms that have the ability to accurately classify the sport practiced […]

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Changes in Lifestyle and Body Weight among Children with Overweight and Obesity

In Canada, about one third of children aged 5 to 17 years are overweight, and 12% have obesity – a number that has tripled over the past 50 years. Childhood obesity is associated with increased risk of several comorbidities, including type 2 diabetes, low self-esteem, depression, and cardiovascular disease. In an era of personalized medicine, […]

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Développement d’un algorithme de classification des nuages de points lidar aéroporté par apprentissage profond

La compagnie XEOS Imagerie oeuvre dans le domaine de l’acquisition de données lidar (Light Detection and Ranging). Elle désire extraire automatiquement les points associés au sol et aux objets à partir du nuage de points 3D brut de l’acquisition lidar. La procédure actuelle pour classifier les points repose sur une combinaison d’algorithmes spécialisés et d’interprétation […]

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