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Head of the Research Department Interactive Machine Learning

Prof. Dr.-Ing. Daniel Sonntag

Publications

Hannes Kath; Thiago Gouvea; Daniel Sonntag

In: Dietmar Seipel; Alexander Steen (Hrsg.). KI 2024: Advances in Artificial Intelligence. German Conference on Artificial Intelligence (KI-2024), 47th German Conference on AI, Würzburg, Germany, September 25–27, 2023, Proceedings, located at 47th German Conference on AI, September 25-27, Würzburg, Germany, Germany, LNAI, Springer, Heidelberg, 9/2024.

To the publication

Hannes Kath; Thiago Gouvea; Daniel Sonntag

In: Dietmar Seipel; Alexander Steen (Hrsg.). KI 2024: Advances in Artificial Intelligence. German Conference on Artificial Intelligence (KI-2024), 47th German Conference on AI, Würzburg, Germany, September 25–27, 2023, Proceedings, located at 47th German Conference on AI, September 25-27, Würzburg, Germany, Germany, LNAI, Springer, Heidelberg, 9/2024.

To the publication

Hannes Kath; Patricia P. Serafin; Ivan B. Campos; Thiago Gouvea; Daniel Sonntag

In: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. International Joint Conference on Artificial Intelligence (IJCAI-2024), located at IJCAI, August 03-09, Jeju. International Joint Conference on Artificial Intelligence (IJCAI-2024), August 3-9, Jeju, Korea, Republic of, International Joint Conferences on Artificial Intelligence, 8/2024.

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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
  • Ophthalmo-AI

    Intelligent, Cooperative Medical Decision Support in Ophthalmology

    The goal of Ophthalmo-AI is to develop better diagnostic and therapeutic decision support in ophthalmology through effective collaboration of machine and human expertise (Interactive Machine Learning…

    Ophthalmo-AI
  • pAItient

    Protected Artificial Intelligence Innovation Environment for Patient Oriented Digital Health Solutions for developing, testing and evidence based evaluation of clinical value.

    Developments in recent years, such as low-cost hardware for enormous computing power and machine learning techniques, have given AI new impetus in medicine as well, and in many medical application…

  • XAINES

    Explaining AI with Narratives

    In the XAINES project, the aim is not only to ensure explainability, but also to provide explanations (narratives). The central question is whether AI can explain in one sentence why it acted the way…

    XAINES
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