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Publications

Displaying results 141 to 150 of 658.

  1. Matthias Tschöpe; Stefan Gerd Fritsch; Vitor Fortes Rey; Niranjan Narendra Nandurkar; Sarah Trevenna; Eloise Monger; Paul Lukowicz

    NEEDLE: Nurse Education Enhanced by Vision-based Deep Learning Evaluation

    In: 2025 7th International Conference on Activity and Behavior Computing (ABC). International Conference on Activity and Behavior Computing (ABC), April 21-25, Abu Dhabi, Abu Dhabi, United Arab Emirates, Pages 1-10, IEEE Xplore, 2025.

  2. Matthias Tschöpe; Stefan Gerd Fritsch; David Kariem Habusch; Vitor Fortes Rey; Agnes Grünerbl; Paul Lukowicz

    Evaluating Deep Learning Models for Posture and Movement Recognition During the ABCDE Protocol in Nurse Education

    In: 2024 International Conference on Activity and Behavior Computing (ABC). International Conference on Activity and Behavior Computing (ABC-2024), 6th International Conference on Activity and Behavior Computing, May 28-31, Nakatsu, Japan, Pages 1-10, IEEE, 2024.

  3. Fabian Schmeisser; Maria Caroprese; Gillian Lovell; Andreas Dengel; Sheraz Ahmed

    How to Box Your Cells: An Introduction to Box Supervision for 2.5D Cell Instance Segmentation and a Study of Applications

    In: Proceedings of the 17th International Conference on Agents and Artificial Intelligence. International Conference on Agents and Artificial Intelligence (ICAART-2025), February 23-25, Porto, Portugal, Vol. 3, SciTePress, 2025.

  4. T. Vincent; F. Wahren; Jan Peters; B. Belousov; C. D'Eramo

    Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning

    In: ICML Workshop on Automated Reinforcement Learning. International Conference on Machine Learning (ICML-2024), ICML, 2024.

  5. Ankur Bhatt; Ko Watanabe; Jayasankar Santhosh; Andreas Dengel; Shoya Ishimaru

    ABCDE: Appearance-Based Confidence Detection by Evaluating Gaze Behavior Using Deep Learning

    In: International Journal of Activity and Behavior Computing, Vol. 2025 1, Pages 1-24, Care XDX Center, Kyushu Institute of Technology, 7/2025.

  6. Tim Dahmen; Niklas Rottmayer; Katja Schladitz; Markus Kronenberger; Ziwei He; Miriam Hommel; Petra Gospodnetic; Claudia Redenbach

    Combining Stochastic Geometry and Neural Models of Electron Matter Interaction for the Simulation of Electron Imaging of Porous Materials

    In: Proceedings of the XI International Conference on Coupled Problems in Science and Engineering. International Conference on Coupled Problems in Science and Engineering (Coupled Problems-2025), May 25-28, Villasimius, Sardinia, Italy, IACM, 2025.

  7. Théo Vincent; Tim Lukas Faust; Yogesh Tripathi; Jan Peters; Carlo D'Eramo

    Eau De Q-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

    In: Proceedings of the 2nd Reinforcement Learning Conference 2025. Reinforcement Learning Conference (RLC-2025), August 5-9, Edmonton, AB, Canada, Reinforcement Learning Journal (RLJ), 2025.

  8. Snehal Walunj; Nazanin Mashhaditafreshi; Parsha Pahlevannejad; Achim Wagner; Martin Ruskowski

    Human-Robot Interaction Through Egocentric Hand Gesture Recognition

    In: Kosmas Alexopoulos; Sotiris Makris; Panagiotis Stavropoulos (Hrsg.). Advances in Artificial Intelligence in Manufacturing II. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2024), Cham, Pages 125-133, ISBN 978-3-031-86489-6, Springer Nature Switzerland, 2025.

  9. Vinit Vikas Hegiste; Tatjana Legler; Martin Ruskowski

    Collaborative Learning in Shared Production Environment Using Federated Image Classification

    In: Kosmas Alexopoulos; Sotiris Makris; Panagiotis Stavropoulos (Hrsg.). Advances in Artificial Intelligence in Manufacturing II. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2024), Cham, Pages 98-106, ISBN 978-3-031-86489-6, Springer Nature Switzerland, 2025.

  10. Christoph Peter Balada; Aida Romano-Martinez; Vincent ten Cate; Katharina Geschke; Jonas Tesarz; Paul Claßen; Alexander K Schuster; Dativa Tibyampansha; Karl-Patrik Kresoja; Philipp S Wild; others

    Deep Learning for Cardiovascular Risk Assessment: Proxy Features from Carotid Sonography as Predictors of Arterial Damage

    In: Lecture Notes in Computer Science. Medical Image Understanding and Analysis (MIUA-2025), LNCS, Springer Nature, 2025.

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