The Home of Machine Learning at Leibniz University Hannover

  • Our work “Robust Shape Fitting for 3D Scene Abstraction” has been accepted for publication in the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).

The “Institut für Informationsverarbeitung” (Institute for Information Processing) is the home of machine learning at the Leibniz University Hannover. We focus on three main research directions, namely (I) computer vision & representation learning, (II) signal processing & -coding and (III) automated machine learning. Our methods range from deep learning, automated machine learning, reinforcement learning, image analysis, remote sensing and compression of audio, image, video as well as DNA to biomedical data. Our efforts are directed towards making efficient use of multi-modal and high dimensional data for reliable predictions, ultimately supporting end-users, developers and decision makers in a vast range of applications.

Since the foundation in 1973, the institute holds a strong tradition of cultivating connections to industry partners and jointly developing solutions to automatically process and harness information. Some of the developed methodology were successfully spun-off commercially as for instance with driver assistance modules, cochlear implants or component testing. The institute is also well known for being actively involved in the standardization of MP3, MPEG-2, AVC (H.264), HEVC (H.265) as well as MPEG-G.

Do you want to join us? We have open positions.

Current Spotlight
Automatic Speech Recogition for Children's Speech
Automatic speech recogition and analysis of children's speech to support speech therapy and research of speech development. (more...)

AI-Campus: AutoML MOOC
To teach researchers and developers how Automated Machine Learning (AutoML) can be used and further developed, we offer an AutoML-MOOC at the ai-campus.org. (more...)


TNT
"Als Doktorandin am Institut profitiere ich nicht nur von der herausragenden Forschungsinfrastruktur, sondern auch von einem unterstützenden und inspirierenden akademischen Umfeld, das meine wissenschaftliche Neugier beflügelt. Ich kann das Institut angehenden Forscherinnen und Forschern wärmstens empfehlen, die in einem dynamischen und interdisziplinären Umfeld ihr volles Potenzial entfalten möchten."
Stephanie Kristin Schröder