Sven Lange, M.Sc.

Sensorik (SEN)

Wissenschaftlicher Mitarbeiter

Nahfeldscanner, Ortung und KI-Anwendungen

E-Mail:
lange@sensorik.uni-paderborn.de
Telefon:
+49 5251 60-5643
Web:
Homepage
Büro­anschrift:
Pohlweg 47-49
33098 Paderborn
Raum:
P6.2.3

Publikationen

Aktuelle Publikationen

A Hybrid Data Generation Approach for the Development of an AI-based EMC Interference Recognition Method

S. Lange, M. Olbrich, D. Hemker, J. Maalouly, J. Kutter, D. Schröder, C. Hedayat, M. Kleinen, A. Grünwaldt, J. Bärenfänger, H. Mathis, H. Kuhn, in: 2024 International Symposium on Electromagnetic Compatibility – EMC Europe, IEEE, Bruges, Belgium, 2024.

DOI

Evaluation of Simulated and Real Measurement Data for AI-based Interference Classification in EMC Applications

J. Maalouly, D. Hemker, S. Lange, M. Olbrich, C. Hedayat, J. Kutter, H. Mathis, in: 2024 International Symposium on Electromagnetic Compatibility – EMC Europe, IEEE, Brugge, Belgium , 2024.

DOI

Enhancing Information Extraction in EMC Measurements through Artificial Intelligence

M. Stiemer, S. Lange, D. Schröder, C. Hedayat, J. Maalouly, D. Hemker, H. Mathis, in: 2024 Smart Systems Integration Conference and Exhibition (SSI), IEEE, Hamburg, 2024.

DOI

Characterization of Various Environmental Influences on the Inductive Localization

S. Lange, U. Hilleringmann, C. Hedayat, H. Kuhn, J. Förstner, in: 2023 IEEE Conference on Antenna Measurements and Applications (CAMA), IEEE, Genoa, Italy , 2023.

DOI

AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development

J. Maalouly, D. Hemker, C. Hedayat, C. Rückert, I. Kaufmann, M. Olbrich, S. Lange, H. Mathis, in: 2022 Kleinheubach Conference, IEEE, Miltenberg, Germany, 2022.


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