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Dr.-Ing. Michael Johannes Barz

Organizational unit Interactive Machine Learning
Contact +49 681 85775 4819 (Saarbrücken)

Address (Saarbrücken) Gebäude D3 1Stuhlsatzenhausweg 366123 Saarbrücken

Publications

All publications
  1. InFL-UX: A Toolkit for Web-Based Interactive Federated Learning

    Tim Maurer; Abdulrahman Mohamed Selim; Hasan Md Tusfiqur Alam; Matthias Eiletz; Michael Barz; Daniel Sonntag

    In: Companion Proceedings of the 17th ACM SIGCHI Symposium on Engineering Interactive Computing Systems. ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS-2025), 17th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, located at EICS-2025, June 23-27, Trier, Germany, Pages 65-67, EICS '25 Companion (EICS '25 Companion), ISBN 9798400718663, Association for…

Profile

  • No-IDLE

    Interactive Deep Learning Enterprise

    In recent years, machines have surpassed humans in the performance of specific and narrow tasks such as some aspects of image recognition or decision making along clinical pathways in the medical…

    No-IDLE
  • MASTER

    MASTER: Mixed reality ecosystem for teaching robotics in manufacturing

    Many industries are transitioning to Industry 4.0 production models by adopting robots in their processes. In parallel, Extended Reality (XR) technologies have reached sufficient maturity to enter the…

    MASTER
  • SciBot

    Data Science Chatbot: A text-based interface, that learns from experts to support experts

    The goal of this project is the development of efficient methods for analyzing and for learning to analyse the user behavior during interactions with an expert system. The considered scenario includes…

    SciBot
  • GeAR

    Gelingensbedingungen und Grundsatzfragen von Augmented Reality in experimentellen Lehr-Lernszenarien

    In Augmented Reality the real world is extended by additional information. Already common areas of application are navigation or the transmission of sports events such as football or ski jumping.…

    GeAR