About Data Extraction
A major challenge of current (big) data systems lies in the provision of high-quality information suited for downstream analysis purposes, given that the data at hand are often irrelevant, redundant, noisy, inconsistent, incomplete or unstructured.
Imec research groups at UGent and KU Leuven are devising innovative cleansing, completion and feature extraction approaches to extract reliable information from raw data.
How can we help you?
Some examples of what we have done
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Join the forward thinkersJob opportunities
AI-based prediction of agitation in dementia patients
Leveraging advanced wearable and remote health parameter sensor technologies with contextual sensing and the power of machine-learning to improve the care for and quality of life of patients with dementia.
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Neural network based approach to design complex PV systems
to develop and implement data-driven approaches for modelling and optimizing the long-term outdoor performance of complex PV systems
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Apply reliability physics to develop hardware implementations for more lightweight security solutions as well as improved robustness against post-quantum cryptographic threats
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