Speaker
Prof.
André Hinkenjann
(Hochschule Bonn-Rhein-Sieg, Institut für Visual Computing)
Description
To support visual analytics of large radio/volume data, we accelerated a source finding/filtering algorithm by employing GPUs. Also, we implemented a GPU based volume renderer that achieves real-time performance and can be used in interactive environments, like an Augmented Reality setup. When visually analysing unfiltered data the frame rates of the renderer drop significantly and data is often too big to fit onto GPUs. Very first tests with a neural representation of noisy volumes to reduce storage requirements show that there is a tradeoff between quality and efficiency. We would like to learn more about DL based representation of noisy volume data.
