Suicide is one of the most important causes of deaths in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years. To address this problem, there is a real and immediate need for an automated, private, and effective monitoring system that can […]

The project is part of a desire to address the school dropout issue, particularly in multi-ethnic and disadvantaged communities. Despite the implementation of several universal interventions in Quebec, the drop-out rate remains high in numerous areas. In the Eastern Townships area, a partnership between the Sherbrooke Regional School Board and the Université de Sherbrooke in […]

Recent advances in machine vision has led to new opportunities for automating that entire manufacturing pipeline. Consider, for example, the situation where an unattended computer vision system inspects the widget and decides whether or not to discard it. Even this little amount of automation can save many hundreds of person-hours on a typical factory floor. […]

The goal of the project is to evaluate several clustering algorithms on players’ styles data in the context of Video Lottery Terminals (VLTs). The previous work has shown that by segmenting anonymous player data by sessions, and then clustering the sessions using the simple k-means algorithm, we can get a descriptive statistic on player styles, […]

Editing the faces of 3D avatars is a difficult and important task. We will develop an approach that enables users to perform local edits of faces through means of adjusting the values of anthropometric measurements. Such measurements are derived from well-established research about the shape and proportion of faces. Based on a data set of […]

Locating and identifying multiple individuals in a scene are challenging tasks in real-time video surveillance applications. Although tracking allows to locate a person over time, automatically tracking multiple targets under real-world conditions is a challenging problem due to changes in appearance, occlusions and complex backgrounds. Target models are typically adapted for robust discriminative tracking, although […]

In this project, the goal is first to design a domain ontology that models the innovation management forms semantically. At this step, the ontology contains domain-specific background knowledge, which is expressed using terminological statements. Then every completed form and the value of its fields are asserted as instances of different concepts of the ontology. Afterwards, […]

This proposed study will significantly enhance our current understanding of how specific intra-operative factors can impact patient outcomes. Our proposed work will provide a proof of concept that machine learning can objectively predict a specific, high-impact post-operative complication, allowing us to move forward with scaling this work to a wide variety of surgical settings. Moreover, […]

Hospitals strive to perform cutting edge medical treatment, treat all patients fairly, and reduce operating costs, while also enabling caregivers to spend more time interacting with patients. Artificial intelligence and machine learning promise these things. However, medical data provides unique challenges for machine learning. Currently, if a hospital wants to include an algorithm for automated […]

Anticoagulation with Warfarin is indicated and required for post-operative cardiovascular patients. However, it is a high-risk medication with a narrow therapeutic range where sub-optimal dosing can lead to complications and even death. While multiple risk factors have been associated to Warfarin sensitivity, the prediction of optimal Warfarin dosing strategies remains ineffective and requires trial and […]

The research will be using visual information from the phone’s camera as well as demographic information from participants and implement various machine learning algorithms such as random forests, support vector machines, etc. to provide feedback regarding different exercises to the participant. Specifically, the algorithms will classify the exercise types. Furthermore, these algorithms will be optimized […]

Healthcare facilities collect and produce vast amounts of clinical-relevant data. Various AI-related methods (like computer-aided detection for mammography and the learning and visualization of clinical pathways) are applied to healthcare these days, and visualization techniques are also used to support clinicians due to the complexities of clinical data. This self-contained survey focuses on the assessment […]