Informatik,
Maschinelles Lernen,
Datenanalyse,
Vernetzte Systeme,
IoT,
Bildverarbeitung,
KI/Künstliche Intelligenz (Computer Science - Machine Learning - Data Science - Distributed Systems - IoT - Computer Vision - Artificial Intelligence)

Deep Learning, Zeitreihenanalyse, Interaktives Lernen von Modellen, Datenanforderungen von ML-Methoden, Lernen unter Daten- und Annotationsmangel (Deep Learning, Time Series Analysis, Interactive Learning of Models, Data requirements for Machine Learning, Learning with Data and Annotation Scarcity)

http://www.erodner.de

• Projekte (12)
• Publikationen (23)
• Patente (2)
• Preise / Auszeichnungen (4)
• Begutachtungen (1)
• Mitgliedschaften (2)
• Creative Computing
  (Forschungscluster)
• Gesundheit
  (Forschungscluster)

Erik Rodner is a researcher in the field of computer vision and machine learning, and his work focuses on developing algorithms and models to enable machines to understand and interpret visual data. Some of his research contributions include the development of deep learning architectures for object recognition and semantic segmentation, the use of weakly-supervised and self-supervised methods to improve annotation efficiency, and the integration of domain-specific knowledge to improve the robustness of vision systems. His research has been published in several well-respected journals and conferences. Overall, Erik Rodner's research aims to push the boundaries of what machines are capable of perceiving and understanding from visual data, and to make these capabilities more widely available for practical applications.

• ​Campus Story zum Programmierprojekt​
• ​Informationen zur Durchführung von Abschlussarbeiten (HTW-Intern)​
• ​KI-Werkstatt​
• ​Vorlesungen in der KI-Werkstatt​

Termine können jederzeit per e-Mail vereinbart oder Calendly (https://calendly.com/rodner/sprechstunde) vereinbart werden // Please contact me by e-mail or use the calendly link above to arrange a meeting.

• Ingenieurinformatik (B)
  Hochschullehrer*in, Praktikumsbeauftragte*r
• Informatik in Ingenieurwissenschaften (M)
  Hochschullehrer*in
• Fachbereich 2: Ingenieurwissenschaften - Technik und Leben
  Hochschullehrer*in