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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Senior Data Scientist
Data Wizard who dreams to create applicable solutions for protecting our globe!
Driving digital innovation in mental health applications
Explore the potential of wearable sensor data towards understanding mental health
Introduction of EDS analysis into TEM automation.
Bringing chemical analysis into the CMOS industry for high throughput and precision by automated electron microscopy.
Data analysis on in-vitro neuronal network electrophysiology
Help scientists unravel brain function by using imec's state-of-the-art medical devices
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