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Projects

Displaying results 1 to 7 of 7.
  1. NoIDLEChatGPT – No-IDLE meets ChatGPT

    NoIDLEChatGPT – No-IDLE meets ChatGPT

    Das Projekt "No-IDLE meets ChatGPT" zielt darauf ab, die Mensch-Maschine-Interaktion bei der Aktualisierung von Deep-Learning-Modellen (DL) zu verbessern, indem die Mensch-Computer-Interaktion (HCI) m

  2. TwinMaP – Digital twin of a heterogeneous machine park for the complete machining of components

    TwinMaP – Digital twin of a heterogeneous machine park for the complete machining of components

    The TwinMaP project focuses on the development of innovative concepts for digital twins of factory workers in assembly and pre-assembly. While other partners integrate digital twins of machines and sy

  3. No-IDLE – Interactive Deep Learning Enterprise

    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 doma

  4. MOMENTUM – Robust Learning with Hybrid AI for Trustworthy Interaction of Humans and Machines in Complex Environments

    MOMENTUM – Robust Learning with Hybrid AI for Trustworthy Interaction of Humans and Machines in Complex Environments

    MOMENTUM is a research project dedicated to TRUSTED-AI, which aims to advance the development and application of artificial intelligence by integrating robustness and explainability. The aim of the pr

  5. Adra-e – AI, Data and Robotics ecosystem

    Adra-e – AI, Data and Robotics ecosystem

    Adra-e - Supporting the AI, Data and Robotics Community in the Development of a Sustainable European Ecosystem Adra-e is a Coordination and Support Action (CSA) funded by the European Commission under

  6. STAR – Safe and Trusted Human Centric ARtificial Intelligence in Future Manufacturing Lines

    STAR – Safe and Trusted Human Centric ARtificial Intelligence in Future Manufacturing Lines

    STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe and reliable human-centric AI systems in real-life manufacturing environme

  7. RACKET – Rare Class Learning and Unknown Events Detection for Flexible Production

    RACKET – Rare Class Learning and Unknown Events Detection for Flexible Production

    The RACKET project addresses the problem of detecting rare and unknown faults by combining model-based and machine learning methods. The approach is based on the assumption that a physical or procedur