Prof. Dr. Veniamin Morgenshtern

Maschinelles Lernen in der Bild- und Signalverarbeitung:
- Konvexe Optimierung und Sparsity
- Theorie und Anwendungen von Deep Learning
- Teilüberwachtes maschinelles Lernen
Anwendungen:
- Super-auflösende Mikroskopie und Radar
- Bilderkennung für autonom fahrende Autos
- Ultra-zuverlässige Bildverarbeitung für mikrofluidische medizinische Systeme

Profile im Web:

FAU Maps: A wealth of knowledge in AI and energy and climate 27. January 2020

The 21st century poses considerable challenges to mankind, and science has a major role to play in mastering them. Researchers at FAU also have a valuable contribution to make. The University has now launched two Maps focussing on its expertise in two areas which are particularly important for society: the...

Could artificial intelligence assist decision-making in clinical practice? 12. November 2019

Artificial intelligence (AI) is becoming more common in clinical practice. Increased computing power, greater volumes of data generated, and progress in machine learning promise new possibilities in clinical research and patient care. However these developments also raise certain ethical and legal questions. How will the role of doctors and patients...

Using AI to make assistance systems more intelligent for real-life situations 12. November 2019

FAU doctoral candidate Annette Hagengruber has set herself the goal of designing solutions based on artificial intelligence to help people with restricted mobility in their everyday lives. The Gesellschaft für Informatik e.V. (German Informatics Society) has nominated her as an AI newcomer of the year in recognition of her achievements....

Medical imaging: same quality, less time 7. November 2019

Elisabeth Hoppe is completing a doctoral degree at FAU in the area of quantitative MR imaging in combination with deep learning and has developed a deep learning based reconstruction method for the quantitative imaging technique magnetic resonance fingerprinting. In recognition of her research, the scientist from the Pattern Recognition Lab...