Learning vision is easy?

10 May 2022, 17:00:00
Creek Street
Linköping

The visual cortex is a  major area in the human brain and the majority of input from the  environment is perceived by vision. Still, it was believed for decades  that computer vision is a simple problem that can be  addressed by student projects or clever system design based on concepts  from related fields. About a decade ago, the field observed a major  breakthrough with the advent of deep learning, to a large extent enabled  by means of novel computational resources in  form of GPUs.

Since then, the field  basically exploded and thousands of black-box approaches to solve vision  problems have been developed. However, it turned out that previously  known concepts such as uncertainty and geometry  are still relevant when we want to better understand deep learning  methods and achieve state of the art performance.

Learning vision is easy?

Michael Felsberg

Michael has  gotten his PhD in Computer Vision from Christian-Albrechts Universtät  in Germany and his Professor in Computer Vision at Linköping University.  In 2018 he was awarded the highest ranked  AI researcher in Sweden.

Now he is working on a wide  range of topics within artificial visual systems, such as  three-dimensional computer vision, computational imaging, object  detection, tracking and recognition, robot vision and autonomous  systems.