Intelligente Eingebettete Systeme - Forschungsinformationssystem | Universität Kassel - CONVERIS Forschungsinformationsystem

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Intelligente Eingebettete Systeme (IES)

Universität Kassel » Fachbereiche » FB 16 - Elektrotechnik / Informatik » Informatik

Telefon:

+49 (0)5 61 / 8 04-60 20

Fax:	+49 (0)5 61 / 8 04-60 22

Adresse:

Wilhelmshöher Allee 73
34121 Kassel

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Projekte

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3 von 4

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04/2016 - 12/2017	Computational Intelligence für Offboard-Diagnosesysteme
01/2016 - 12/2018	Detection Intentions of Vulnerable Road Users Based on Collective Intelligence as a Basis for Automated Driving - Phase 1 (Teilprojekt zu SPP 1835: Kooperativ interagierende Automobile)
06/2015 - 12/2019	Techniken des Organic Computing für die Laufzeit-Selbst-Adaption ubiquitärer, multi-modaler Kontext- und Aktivitätserkennungssysteme
04/2015 - 12/2017	Big Data Analytics for Renewable Energy Related Time Series
01/2015 - 12/2017	Probabilistische innovative Methoden in der Energiesystemtechnik
01/2015 - 12/2016	Securing Cyber-Physical Systems with Organic Computing Methods - Phase 1
10/2013 - 02/2014	Entwicklung eines Systems zum Lernen von Benutzerverhalten und zum Antizipieren von Benutzerwünschen
12/2012 - 12/2012	Spende für Kinematik-Sensorsystem bzw. Spende für Kasseler Informatik Kolloquium (KIK)
09/2012 - 03/2013	Vorstudie zur Entwicklung von adaptiven Kundenfunktionen
08/2012 - 12/2012	Spende für Lehre und Forschung des Fachgebietes IES

Publikationen

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1 von 13

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2024	Baum, E., Liu, Z., Stursberg, O., 2024. Distributed State Estimation of Linear Systems With Randomly Switching Communication Graphs. IEEE Control Systems Letters 8, 1781–1786. https://doi.org/10.1109/LCSYS.2024.3414977
2024	Huseljic, D., Herde, M., Rauch, L., Hahn, P., Huang, Z., Kottke, D., Vogt, S., Sick, B., 2024. Efficient Bayesian Updates for Deep Learning via Laplace Approximations. NeurIPS. https://doi.org/10.48550/arXiv.2210.06112
2024	Huang, Z., Gruhl, C., Sick, B., 2024. LiST: An All-Linear-Layer Spatial-Temporal Feature Extractor with Uncertainty Estimation for RUL Prediction, in: IEEE (Hrsg.), 2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), 5-8 Aug. 2024. IEEE, Piscataway, NJ, S. TBD. https://doi.org/10.1109/ICIEA61579.2024.10665236
2024	Nivarthi, C.P., Huang, Z., Gruhl, C., Sick, B., 2024. Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection, in: IEEE (Hrsg.), 2024 International Joint Conference on Neural Networks (IJCNN) : IJCNN 2024 Conference proceedings. IEEE, Piscataway, NJ, S. TBD. https://doi.org/10.1109/IJCNN60899.2024.10651344
2024	Braun, M., Gruhl, C., Hans, C.A., Härtel, P., Scholz, C., Sick, B., Siefert, M., Steinke, F., Stursberg, O., Wende-von Berg, S., 2024. Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems, in: IEEE (Hrsg.), IEEE PES ISGT Europe 2024 : Conference book : 14-17 October 2024, Dubrovnik, Croatia. IEEE, Piscataway, NJ, S. TBD. https://doi.org/10.1109/ISGTEUROPE62998.2024.10863480
2024	He, Y., Huang, Z., Vogt, S., Sick, B., 2024. PrOuD: Probabilistic Outlier Detection Solution for Time-Series Analysis of Real-World Photovoltaic Inverters. Energies 17, TBD. https://doi.org/10.3390/en17010064
2024	Huang, Z., He, Y., Nivarthi, C.P., Gruhl, C., Sick, B., 2024. Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction, in: IEEE (Hrsg.), IJCNN 2024 Conference Proceedings, 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, Piscataway, NJ, S. TBD. https://doi.org/10.1109/IJCNN60899.2024.10650622
2024	Huang, Z., He, Y., Nivarthi, C.P., Sick, B., Gruhl, C., 2024. Time-Series Representation Learning via Heterogeneous Spatial-Temporal Contrasting for Remaining Useful Life Prediction, in: Antonacopoulos, A., Chaudhuri, S., Liu, C.-L., Bhattacharya, S., Pal, U. (Hrsg.), Pattern Recognition : 27th International Conference, ICPR 2024, Kolkata, India, December 1–5, 2024, Proceedings, Part XXVII. Springer Nature, Cham, S. 1–21. https://doi.org/10.1007/978-3-031-78398-2_1
2023	Huang, Z., He, Y., Herde, M., Huseljic, D., Sick, B., 2023. Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. CEUR Workshop Proceedings 3470, 25–45.
2023	Akhundzada, S., Dingel, K., Bischof, D.J.B., Janzen, C., Sick, B., Ehresmann, A., 2023. Domain Imaging in Periodic Submicron Wide Nanostructures by Digital Drift Correction in Kerr Microscopy. Advanced Photonics Research 4, 2300170. https://doi.org/10.1002/adpr.202300170