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advanced visual perception methods for reliable object detection, scene understanding, and interaction under adverse environment conditions. The goal is to enable fully autonomous execution of complex
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visualization of large geospatial datasets. Translating research data and results into applications supporting sustainable water management and environmental monitoring. Publishing in peer-reviewed scientific
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environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software
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in applied optimization • Knowledge of digital twins • Experience in data analysis and visualization. Minimum requirements: • Experience in Python; • Knowledge of optimization algorithms; • Knowledge
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provide important analytical foundations, ROADS combines these approaches with ethnographic, archival, visual, and artistic methods. The project therefore welcomes applicants interested in methodological
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for the automatic detection of pulmonary nodules on CT are one of the most studied applications. Although these systems improve the performance of radiologists, they usually only allow visual description
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Explore machine learning approaches for discovering interpretable and clinically relevant visual representations.; • Validate the proposed methodologies
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; • Experience in data analysis and visualization. Minimum requirements: • Experience in Python; • Knowledge of optimization algorithms; • Knowledge of modelling or simulation. 5. EVALUATION OF APPLICATIONS AND
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1547, UL 1741, ENTSO-E / NC RfG, EN 50549 UL 1741 & UL 9540 (PCS-ESS) IEC 61850, 62443, etc. Engage the industry research collaborators in the guided development of the project milestones, deliverables
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, text-based image retrieval, and visual question answering. Their application in remote sensing for semantic understanding of objects and relationships is a growing research field. This is an exciting