This research will explore the possible use of video analysis, object detection, and machine learning models to identify TV commercials and advertisements in real-time on low-power computer systems. The partner organization focuses on software development and advertisement technology. The partner aims to solve the challenge of developing a lightweight power-efficient AI-based software that would be […]

Cancer’s persistent prevalence calls for innovative steps in early detection and therapeutic interventions. Metabolomics offers a comprehensive view of the metabolites that measure the function of cellular processes in this context. As explainable AI (XAI) emerges, it sheds light on these intricate systems’ decision-making processes and outcomes, making them accessible to human understanding. The project […]

Computer Algebra Systems (CAS), with their unique ability to analyze and solve mathematical problems, are gathering new communities of users, who challenge those software systems with more and more complex tasks. It is necessary, therefore, that the core engines of CAS to implement state-of-the-art algorithms. This proposal capitalizes on the research conducted by academic partners […]

This research project aims to tackle the challenge of ensuring the reliability of large-scale software systems, which are crucial for various applications such as online services and data processing. The project focuses on developing cost-effective and intelligent methods for monitoring these systems to anticipate and prevent runtime incidents, such as crashes or errors, which can […]

The rise of Big Data, social networking, and mobile interactions coupled with an accelerating increase in the amount of structured and unstructured information enabled by cloud based technologies is forcing organizations to focus on information that is most relevant, value-generating, and risk-related. Problems arise when we make decisions based on good enough metrics (e.g. means) […]

We are seeking an intern to join our company and assist in enhancing our reporting efficiency and productivity through Power BI. Currently, our company gains insights into efficiency and productivity using various tools, including Autotask, Project for the Web, and Excel spreadsheets. However, we aim to leverage this data with Microsoft Power BI to create […]

Numerous barriers exist to participating in sports, and a study by the Canadian Fitness and Lifestyle Research Institute has shown that 12% of respondents cited not having anyone to participate with as an obstacle. (Canadian Fitness and Lifestyle Research Institute, 2013). With this project, we aim to leverage algorithms and artificial intelligence (AI) to better […]

ASETS-CA is an upcoming startup with a product that is called ASETS Integrated Design Suite (IDS) a cloud-based 3D facility modelling tool. This tool has a front- end and backend which needs to be tested rigorously before it goes out to the customer with different variation as per their needs. As per industry standards all […]

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This project aims to enhance Aview International’s platform by adding advanced real-time translation, live streaming support, and real-time dubbing capabilities. These new features will allow content creators to broadcast their content live in multiple languages simultaneously, breaking down language barriers and making their content accessible to a global audience. This will significantly expand Aview International’s […]

Self-supervised representation learning (SSRL) has advanced considerably by exploiting the transformation invariance assumption under artificially designed data augmentations. While augmentation-based SSRL algorithms push the boundaries of performance in computer vision and natural language processing, they are often not directly applicable to other data modalities, and can conflict with application specific data augmentation constraints. This project […]

Our research project focuses on monitoring crops using satellite images. To address the problem, we leverage a fast-growing field of graph signal processing (GSP), which expands upon traditional signal processing techniques such as Fourier transform and wavelets to accommodate the graph domain. Specifically, we propose to unroll a designed graph-based algorithm into an interpretable feed-forward […]