About Data Visualisation
Data visualization plays an important role in data exploration – both to enable deep insight in that data, and to generate new hypotheses. These visualizations can be aimed at a multitude of endpoints, ranging from (small or large) 2D displays, to autostereoscopic displays, light field displays and – as the holy grail – holographic representations, and can be static or allow for rich user interaction (brushing, filtering, etc).
With increasing size and complexity of datasets, the challenge of computational and perceptual scalability needs to be addressed, both for static representations and for interactive ones. Imec research groups at UAntwerpen, KU Leuven and VUB alleviate this issue by distributed storage and computing as well as compression and visualization of the multimodal source data.
How can we help you?
Some examples of what we have done
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Reliability-physics based hardware primitives for tamper-free cryptographic applications
Apply reliability physics to develop hardware implementations for more lightweight security solutions as well as improved robustness against post-quantum cryptographic threats
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.
Can AI Support Objective Assessment Pain?
AI is becoming a promising tool for modern precision medicine, supporting and in some cases outperforming traditional medical practice.
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 systemsMore job opportunities