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Prof. Dr. Martin Atzmüller

Organizational unit Plan-Based Robot Control
Contact

Address (Osnabrück)

Publications

SHAP value-based ERP analysis (SHERPA): Increasing the sensitivity of EEG signals with explainable AI methods

Sophia Sylvester; Merle Sagehorn; Thomas Gruber; Martin Atzmueller; Benjamin Schöne

In: Behavior Research Methods, Pages 1-15, Springer, 2024.

To the publication

A Neuro-Symbolic Approach for Anomaly Detection and Complex Fault Diagnosis Exemplified in the Automotive Domain

Tim Bohne; Anne-Kathrin Patricia Windler; Martin Atzmueller

In: Brent Venable; Daniel Garijo; Brian Jalaian (Hrsg.). Proceedings of the 12th Knowledge Capture Conference 2023. International Conference on Knowledge Capture (K-Cap-2023), December 5-7, Pensacola, FL, USA, Pages 35-43, K-CAP '23, Vol. 12, ISBN 979-8-4007-0141-2, Association for Computing Machinery, New York, NY, USA, 12/2023.

To the publication

Enhanced Explanations for Knowledge-Augmented Clustering using Subgroup Discovery

Maciej Szelążek; Dan Hudson; Szymon Bobek; Grzegorz J. Nalepa; Martin Atzmueller

In: 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA). International Conference on Data Science and Advanced Analytics (DSAA-2023), October 9-13, Thessaloniki, Greece, Pages 1-11, IEEE, 11/2023.

To the publication
All publications

Profile

  • ExPrIS

    Knowledge-Level Expectations as Priors for Object Interpretation from Sensor Data

    "What will I see when I turn this corner?"

    Depending on what is around that corner, this question is easy for us to answer. We are likely to see a refrigerator in a kitchen, ships at a port, and a…

    ExPrIS

  • AW4.0

    Autowerkstatt4.0

    In the project Autowerkstatt 4.0 (AW 4.0), a consortium consisting of companies and research institutes is developing a platform for the trustworthy data exchange of industry-specific AI models and…

    AW4.0