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Seed project: ODXVR x NTS The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) was to submit an external funding application.…
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Seed project: European spruce bark beetles; advanced predictive forecasting by means of machine learning The main objective for this seed project within Linnaeus University Centre for Data Intensive…
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Seed project: IoT for ships – an untapped data resource The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is to establish…
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Seed project: A platform to collect and analyze canoe/kayak training data The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA)…
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Seed project: Investigate Machine Learning Techniques for Decision-Making Support in K-12 Educational Context The main aim of this seed application is to investigate the use and application of Machine…
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Project: Modelling institutional dynamics in historical commons (MIDI) The MIDI project adopted an interdisciplinary perspective to contribute empirically-grounded and systematic knowledge of the…
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Seed project: User performance data from a video-based application/platform The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and Applications…
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Linnaeus University Centre for Data Intensive Sciences and Applications The DISA research centre at Linnaeus University focuses its efforts on open questions in collection, analysis and utilization of…
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Project: Experiences of digital patient history recording The scientific purpose of this project is to investigate in what way the introduction of digital anamnesis and e-triage affect the quality of…
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Doctoral project: Reuse of health data, combing the best of two worlds A method for automatic generation of features with high predictive power based on domain knowledge.
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Project: Drone measurement for the intelligent forest We are to develop a system for collection of forestry information with drones that fly in the forest below the canopy. Based on video recording,…
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Doctoral project: Advanced identification methods for the forest industry through CV/AI The project intends to create opportunities for continued digitalisation in the forest industry. This concerns…
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Doctoral project: Migration discourse in the Swedish mainstream and social media The project studied migration discourse in the Swedish mainstream and social media in the last decade. Using the…
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Project: In-line visual inspection using unsupervised learning The purpose of this project is to introduce and improve machine learning- assessment of the quality of massproduced industrial (steel)…
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Project: Prediction of medication risks and drug-related problems Medication related problems is a major problem for society, especially with an ageing population and increasing use of medicines. This…
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Doctoral project: AI in administration of agricultural subsidies We want to design, implement and evaluate systems based on artificial intelligence that supports our customer with the administration…
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Seed project:Automated Assembly/Disassembly Instructions (ADDITION) The project aims at building a consortium interested in laying the foundation for harnessing the power of AI and digitalization for…
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Seed project: Using Natural Language Models for Extracting Drug-Related Problems (NLMED) The overall goal of the research in this seed project within the Linnaeus University Center for Data Intensive…