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Publications

Displaying results 221 to 230 of 13730.

  1. Lars Krupp; Steffen Steinert; Maximilian Kiefer-Emmanouilidis; Karina E. Avila; Paul Lukowicz; Jochen Kuhn; Stefan Küchemann; Jakob Karolus

    Challenges and Opportunities of Moderating Usage of Large Language Models in Education

    In: Proceedings of the International Conference on Mobile and Ubiquitous Multimedia. International Conference on Mobile and Ubiquitous Multimedia (MUM-2024), December 1-4, Stockholm, Sweden, MUM '24, ISBN 9798400712838, Association for Computing Machinery, 2024.

  2. Malte Luttermann; Ralf Möller; Marcel Gehrke

    Lifting Factor Graphs with Some Unknown Factors for New Individuals

    In: Zied Bouraoui; Srdjan Vesic (Hrsg.). International Journal of Approximate Reasoning (IJAR), Vol. 179, No. 04/2025 (article 109371), Pages 1-28, Elsevier, 4/2025.

  3. Jibinraj Antony; Dorotea Jalu¨ić; Simon Bergweiler; Ákos Hajnal; Veronika ´labravec; Márk Emődi; Dejan Strbad; Tatjana Legler; Attila Csaba Marosi

    Adapting to Changes: A Novel Framework for Continual Machine Learning in Industrial Applications

    In: Journal of Grid Computing, Vol. 22 (71), Pages 1-19, Springer, 11/2024.

  4. Vinit Hegiste; Tatjana Legler; Martin Ruskowski

    Towards Robust Federated Image Classification: An Empirical Study of Weight Selection Strategies in Manufacturing

    In: 2024 2nd International Conference on Federated Learning Technologies and Applications (FLTA). International Conference on Federated Learning Technologies and Applications (FLTA-2024), September 17-20, Valencia, Spain, Pages 55-62, IEEE, 2024.

  5. Tatjana Legler; Vinit Hegiste; Martin Ruskowski

    Seamless Integration: Sampling Strategies in Federated Learning Systems

    In: 2024 2nd International Conference on Federated Learning Technologies and Applications (FLTA). International Conference on Federated Learning Technologies and Applications (FLTA-2024), September 17-20, Valencia, Spain, Pages 148-155, IEEE, 2024.

  6. Vinit Hegiste; Snehal Walunj; Jibinraj Antony; Tatjana Legler; Martin Ruskowski

    Enhancing Object Detection with Hybrid dataset in Manufacturing Environments: Comparing Federated Learning to Conventional Techniques

    In: 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR). International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR-2024), May 14-15, Muscat, Oman, Pages 1-6, ISBN 979-8-3503-4863-7, IEEE, 2024.

  7. Gregor Duwe; Dominique Mercier; Verena Kauth; Kerstin Moench; Markus Junker; Juan Pablo Vesga; Werner Seiz; Juergen Scheele; Andreas Dengel; Axel Haferkamp; Thomas Höfner

    First preliminary results of artificial intelligence generated treatment recommendations for urothelial cancer based on multidisciplinary cancer conferences from the KITTU project

    In: Annals of Oncology, Vol. 35, No. S2, Pages 1161-1161, ESMO, 9/2024.

  8. Gregor Duwe; Verena Kauth; Kerstin Moench; Dominique Mercier; Markus Junker; Juergen Scheele; Werner Seiz; Oliver Pfante; Juan Pablo Vesga Simmins; Natasja De Bruin; Axel Haferkamp; Andreas Dengel; Thomas Höfner

    KITTU: Artificial intelligence supports multidisciplinary cancer conferences – first steps towards revolutionizing clinical decision making in oncology

    In: Reinhard Büttner (Hrsg.). Oncology Research and Treatment, Vol. 47, No. Supl. 1 - 36. Deutscher Krebskongress - Fortschritt gemeinsam gestalten, Pages 20-20, Karger Publishers, 2/2024.

  9. Oliver Zielinski; Christiane Plociennik; Sebastian Vollmer

    Mit KI an der Stellschraube Nachhaltigkeit drehen

    In: Nachhaltige Industrie, Vol. 3, No. 1, Pages 10-15, Springer Fachmedien Wiesbaden Wiesbaden, 2022.

  10. Ho Minh Duy Nguyen; An T. Le; Trung Q. Nguyen; Nghiem T. Diep; Tai Nguyen; Duy Duong-Tran; Jan Peters; Li Shen; Mathias Niepert; Daniel Sonntag

    Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model

    In: The 16th Asian Conference on Machine Learning. Asian Conference on Machine Learning (ACML-2024), December 5-8, Proceedings of Machine Learning Research, 2024.

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