The Centre for Visual Computing – established in 2011 – lies at the intersection of mathematics and computer science. It seeks mathematical models and their computational solutions towards automatic structuring, processing, and understanding of massive (visual) data with emphasis on optimization, machine learning, inverse problems, and biomedical image analysis.
Image restoration and reconstruction, model-free and model-based segmentation, edge detection, optical flow estimation, object recognition, graphical models, graph mining.
Deep learning, supervised and unsupervised learning, safe AI, sparse modelling, compressed sensing, Bayesian regression, multi-task/online/transfer learning, large-scale optimization, nonconvex optimization.
Tomography, tumor detection, organ segmentation, image registration and fusion, computational anatomy, survival prediction, brain understanding.