Tag: Deep Learning

Every model is wrong, but some models are useful Written by Andreas Maier. We have seen tremendous progress by artificial intelligence (AI) over the past decades. This progress, however, was not achieved steadily. There were significant ups and downs on the way. In some of these phases, peopl...

Over the years, we have collected a rather large collection of online teaching material that we now also highlight on our Teaching Section. One feature is the Deep Learning Material with video lectures and online experimentation environments on various topics. Another gem is the new version of the ...

On Thursday, the 19th of March 2020, we submitted two 3 Million EUR grants to the European Commission. One project aims at building a European Network to establish Book CT as a method to access cultural information in historical books non-invasively from Scanning over Handwritten-Text-Recognition a...

We are proud to announce the funding of "Intelligent MR Diagnosis of the Liver by Linking Model and Data-driven Processes (iDELIVER)“ by BMBF. The project examines the use and further development of machine learning methods for MR image reconstruction and for the classification of liver lesions. Ba...

We just received news that we are able to continue our project on material characterisation using machine learning for another two years. DFG will fund the use of deep learning procedures to determine the forming limits of metal sheets with approximately 150,000 EUR. The project is conducted in coo...

Congratulations to Maniraman Periyasamy, Meike Biendl and Alexander Richter, Jonas Utz, and Henrik Willer for their outstanding achievements in the Deep Learning Challenge 2019! A great success. Please enjoy the backpacks that were donated by Nvidia!

In a cooperation with Marc Kachelriess (DKFZ), Michael Lell (Klinikum Nürnberg Nord) and our lab, we successfully applied for another DFG Project. The aim of the project is to estimate patient-individualised dose for a CT scan using deep learning techniques. In the project, we will unite deep learn...