Institute for Automation and Applied Informatics

Machine Learning for High-Throughput Methods and Mechatronics (ML4HOME)

The research group “Machine Learning for High-Throughput Methods and Mechatronics” (ML4HOME) deals with the analysis of data being generated automatically by mechatronic systems in big amounts. We aim for models based on labeled / unlabeled images or time-series. Our focus is the generalization of big data-sets consisting of a lot of data points (high-throughput), whose extent requires mandatory automatic processing.

To ensure the usability of all developed algorithms and derived knowledge, we integrate our software typically into the open source MATLAB toolbox SciXMiner.

 

Team:

  • PD. Dr. Markus Reischl
  • Moritz Böhland
  • Lukas Klinger (DHBW)
  • Sophie Kramer (PEBA)
  • Friedrich Münke
  • Lisa Petani
  • Prof. Dr. Christian Pylatiuk
  • Jan Schützke
  • Mark Schutera (ZF)
  • Yanke Wang (CSC)

 

Program:

BioInterfaces in Technology and Medicine (BIFTM)

 

Projects:

              

Completed Projects: