Publikationen

Katharina Justmann; Ludwig Leurs; Martin Ruskowski

Mapping of OPC UA FX to the Asset Administration Shell and Capability, Skill and Service Model

In: 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE International Conference on Emerging Technologies and Factory Automation (ETFA-2024), Pages 1-4, IEEE, 2024.

Tatjana Legler; Vinit Vikas Hegiste; Ahmed Anwar; Martin Ruskowski

Addressing Heterogeneity in Federated Learning: Challenges and Solutions for a Shared Production Environment

2024.

Jonas Weigand; Gerben I. Beintema; Jonas Ulmen; Daniel Görges; Roland Tóth; Maarten Schoukens; Martin Ruskowski

State Derivative Normalization for Continuous-Time Deep Neural Networks

In: IFAC-PapersOnLine, Vol. 58, No. 15, Pages 253-258, ELSEVIER, 2024.

Benjamin Blumhofer; Jonas Weigand; Leonhard Kunz; Pascal Rübel; Achim Wagner

Detection of Rare Fault Cases for Mobile Robot Applications

In: Achim Wagner; Kosmas Alexopoulos; Sotiris Makris (Hrsg.). Advances in Artificial Intelligence in Manufacturing. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2023), Cham, Pages 61-70, ISBN 978-3-031-57496-2, Springer Nature Switzerland, 2024.

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.

Vinit Vikas 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.

Tatjana Legler; Vinit Vikas 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.

Vinit Vikas 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.

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.

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.