Institute of Information Theory and Automation

You are here

RNDr. Michal Šorel, Ph.D.

research fellow
Research interests: 
space-variant restoration, image stabilization, deblurring, noise reduction, super-resolution, blind deconvolution, image registration, machine learning, digital image processing and pattern recognition in general
Publications ÚTIA: 

Michal Šorel received the M.Sc. and Ph.D. degrees in computer science from the Charles University in Prague, Czech Republic, in 1999 and 2007, respectively. From 2012 to 2013 he worked on a range of research topics in light-field imaging at the Heriot-Watt University in Edinburgh, Scotland and the University of Bern, Switzerland. Currently he is a research fellow in the Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic. He is a member of the IEEE. Michal Šorel has been a reviewer for the IEEE Transactions on Image Processing, IEEE Transactions on Signal Processing, IEEE Transactions on Pattern Analysis and Machine Intelligence, and several other journals and conferences. He organizes the Spring and Winter Schools of Image Processing. 

2024-05-07 13:24

Person detail

Duration: 2017 - 2019
The basis of the project is the implementation of Industry 4.0 principles during production and repairs of constructional layers of surface transportation.The aim is the automation and optimization of the technological process of measuring and processing data about the surface of ground transportation by virtualization of all technological processes including the establishment of particular metho
Duration: 2016 - 2018
Perfusion analysis is an important experimental technique used for diagnostics and evaluation of therapy response. Analysis based on magnetic resonance (MR) helps in identifying the state and dynamic behaviour of oncological and cardiovascular diseases and enables bettertreatment.
Duration: 2014 - 2017
The goal of the project is to develop a sophisticated software for videokymography (VKG) which will enable automatic evaluation of medical videokymographic recordings of vibrating vocal folds and arrive at correct medical diagnosis. Further goal is to develop a certified method of VKG evaluation to be used in clinical practice.