ML for Automotive Systems:
On Why the System Makes the Corner Case: AI-based Holistic Anomaly Detection for Autonomous Driving,
J. Pfeil, J. Wieland, T. Michalke, A. Theissler (2022),
IEEE Intelligent Vehicles Symposium (IV), 337-344
Link to paper
Predictive Maintenance enabled by Machine Learning: Use cases and challenges in the automotive industry.
Andreas Theissler and Judith Perez-Velazquez and Marcel Kettelgerdes and Gordon Elger (2021).
Reliability Engineering & System Safety, ISSN 0951-8320, vol. 215,
Open Access: Link to paper
Detecting known and unknown faults in automotive systems using ensemble-based anomaly detection. Theissler, A. (2017). Elsevier Journal Knowledge-Based Systems. Vol 123, May 2017, 163-173. Download accepted manuscript , Link to paper
Anomaly detection in recordings from in-vehicle networks. Theissler, A. (2014). Proceedings International Workshop on Big Data Applications and Principles 2014, Madrid. Download , Download
OCADaMi: One-Class Anomaly Detection and Data Mining Toolbox. Theissler A., Frey S., Ehlert J. (2020). In: Machine Learning and Knowledge Discovery in Databases. Proceedings ECML PKDD 2019. Lecture Notes in Computer Science, vol 11908. pages 764-768. ISBN: 978-3-030-46132-4, Springer, Cham. Download preprint , Link to paper
Multi-class Novelty Detection in Diagnostic Trouble Codes from Repair Shops. Theissler, A. (2017). Proceedings IEEE International Conference on Industrial Informatics. 2017. DOI: 10.1109/INDIN.2017.8104917. Download , Link to paper
Detecting anomalies in multivariate time series from automotive systems. Theissler, A. (2013). Brunel University. PhD Thesis. ISBN: 9783843913485
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Interactive Anomaly Detection in time series resulting from local traffic measurements. Theissler, A., Palmer, J. Rehborn, H., Dear, I. (2011).
Proceedings of the IADIS European Conference Data Mining 2011. IADIS Press, Lisbon.
Interactive knowledge discovery in recordings from vehicle tests. Theissler, A., Ulmer, D., Dear, I. (2010).
Proceedings 33rd FISITA World Automotive Congress 2010. FISITA.
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PC-Based Measuring and Test System for High-Precision Recording and In-The-Loop-Simulation of Driver Assistance Functions.
Ulmer, D., Theissler, A., & Hünlich, K. (2010). Embedded World Conference 2010.
Robotics:
Visual Detection of Tiny Objects for Autonomous Robotic Pick-and-Place Operations,
Timo Markert, Sebastian Matich, Daniel Neykov, Markus Muenig, Andreas Theissler and Martin Atzmueller (2022),
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021).
(Best paper award: IES Young Professionals & Students Paper Award)
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Fingertip 6-Axis Force/Torque Sensing for Texture Recognition in Robotic Manipulation.
Timo Markert, Sebastian Matich, Elias Hoerner, Andreas Theissler and Martin Atzmueller (2021).
Workshop Towards the factory of the future: advancements in planning and control of industrial robots.
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021).
(Best paper award: IES Young Professionals & Students Paper Award)
Video
Fault detection and classification in electric, electronic or mechanic systems:
Domain Transfer for Surface Defect Detection using Few-Shot Learning on Scarce Data.
Felix Gerschner, Jonas Paul, Lukas Schmid, Nico Barthel, Victor Gouromichos, Florian Schmid, Martin Atzmueller, Andreas Theissler (2023).
IEEE International Conference on Industrial Informatics (INDIN) 2023.
Evaluation of Machine Learning for Sensorless Detection and Classification of Faults in Electromechanical Drive Systems.
Grüner, T., Böllhoff, F., Meisetschläger, R., Vydrenko, A., Bator, M., Dicks, A., & Theissler, A. (2020). Proceedings 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Procedia Computer Science, Volume 176, pages 1586-1595, 2020, Elsevier. ISSN 1877-0509. Link to paper
In Situ Failure Detection of Electronic Control Units Using Piezoresistive Stress Sensor. Prisacaru, A., Palczynska, A., Theissler, A., Gromala, P., Han, B., & Zhang, G. Q. (2018). IEEE Journal Transactions on Components, Packaging and Manufacturing Technology, 8(5), 750-763. Link to paper
Predictive Maintenance
Predictive Maintenance enabled by Machine Learning: Use cases and challenges in the automotive industry.
Andreas Theissler and Judith Perez-Velazquez and Marcel Kettelgerdes and Gordon Elger (2021).
Reliability Engineering & System Safety, ISSN 0951-8320, vol. 215,
Open Access: Link to paper
Interpretable Machine Learning: A brief survey from the predictive maintenance perspective.
Vollert, Simon and Atzmueller, Martin and Theissler, Andreas (2021).
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021).
Link to paper
Challenges of machine learning-based RUL prognosis: A review on NASA’s C-MAPSS data set.
Vollert, Simon and Theissler, Andreas (2021).
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2021).
Link to paper
Detecting subscribers from Twitch messages:
Detecting potential subscribers on Twitch: A text mining approach with XGBoost Discovery challenge ChAT: CoolStoryBob
Marvin Gärtner, Andreas Theissler, and Marc Fernandes (2020). Proceedings of ECML-PKDD 2020 ChAT Discovery Challenge on Chat Analytics for Twitch. CEUR, Vol-2661, ISSN 1613-0073. Link to paper
Emotion recognition in negotiations:
A deep learning approach to prepare participants for negotiations by recognizing emotions with voice analysis. Jonas Maier, Daniel Schlechte, Marc Fernandes, Andreas Theissler (2020). Local Proceedings International Conference on Group Decision and Negotiation 2020. Download