Personnaliser l’accompagnement de consommateurs dans une plateforme numérique de coaching virtuel

Les Éditions Protégez-Vous souhaitent innover dans la diffusion de leur contenu afin d’accompagner les consommateurs dans leurs choix, en particulier avec une plateforme numérique de coaching virtuel. Une première phase consiste à proposer une plateforme avec le contenu du guide pratique « 100 gestes pour la planète » pour accompagner les consommateurs à faire des […]

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Deep learning approaches for semantic textual similarity on low-resource languages and specialized domains

The aim of this research is to investigate from traditional methods to deep learning methods, how to measure the meaning relationship between two sentences, by combining the local context, at word-level, and the global context at the sentence-level, and their ability to model informativeness and diversity of meanings expressed in natural language, i.e. in English […]

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Indoor Mapping based on recorded videos

Knowledge of indoor spatial information is vital to stores, warehouses, industries, and homes alike. It is used to optimize layouts to achieve easier navigation for humans, machines, and autonomous robots. Maps provide limited data about the specific placement of objects in the environment and inferring information about the physical space can be impossible. The objective […]

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Using AI to generate mining algorithms

Hard-rock mining of uranium in Canada’s north is challenging and often difficult. Operating risk exposures are heightened when mining in high-grade uranium ore bodies that are exposed to possible flooding from water above the mine. To succeed in this environment Cameco has successfully mechanized their operations and relies on Jet Boring technology. This proposed project […]

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AI for delivering product recommendation in retail consumer categories

E-commerce has evolved rapidly in recent decades resulted from globalization and international trade. The demand of online shopping is increasing every day, which has opened business opportunities to attract more costumers locally and globally. However, achieving satisfactory user experience in online shopping remains challenging compared to in-person walk-in shopping. Currently, customers have to input static […]

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Visual-haptic Representation for Zero-shot Learning

Humans recognise objects in the world leveraging multi-modal sensory inputs beyond visual aspects (images and videos). Touch based information (Haptics) possesses rich information about structure, shape and other objetness properties. In this work, we will study and learn cross-modal representations between vision and touch. To connect vision and touch, we plan to introduce a zero […]

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Helping Servus Members Reach Financial Goals via Transfer Learning

In this self-contained project we will investigate how machine learning can be applied to help provide personalized financial advice. Machine learning is a term that designates types of artificial intelligence that rely on learning behaviors from data or experience. Specifically, the goal of this work is to apply machine learning to Servus Credit Union’s Noble […]

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Using a mobile application to support at-risk student re-entry into post-secondary education in the era of COVID-19

The aim of this 2-year project is to do research to inform the development of, and fully test and develop a mobile application designed to improve the experience of (particularly at-risk) post-secondary (PSE) students in addressing COVID-19-related issues. Our key concern is that COVID-19 has not only disrupted important and significant developmental experiences that improve […]

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Power Monitor Load Disaggregation for the Electric Grid

For decades the electric grid has remained a passive system that has delivered electricity to many households and businesses. As utility companies look at converting a passive electric grid to a smart grid, a number of sensors and smart meters must be deployed throughout the grid system to achieve this objective. Deploying vast amounts of […]

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Développement d’un algorithme de reconnaissance d’images de papillons tropicaux

Le nombre d’espèces qui nous entourent est si important qu’il peut être ardu, même pour les spécialistes, de toutes les identifier. Cela est particulièrement vrai pour les insectes. De plus, avec l’avènement des technologies mobiles de l’information, la quantité et la qualité des images disponibles n’a jamais été aussi importante. Grâce aux appareils photos numérique […]

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Interpretable dimensionality reduction of multivariate time series data using LSTM based autoencoders

Data collection over time is a common practice in many large organizations- including financial institutions and health care providers- often with the goal of using this data to predict future challenges and opportunities. While this data may contain valuable information, it is often unstructured, coming from different sources and recorded at different times. This lack […]

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