Sven Lange, M.Sc.

Sensor Technology

Research Associate

Near-field scanner, localization and AI applications

E-Mail:
lange@sensorik.uni-paderborn.de
Phone:
+49 5251 60-5643
Web:
Homepage
Office Address:
Pohlweg 47-49
33098 Paderborn
Room:
P6.2.3

Publications

Latest Publications

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

Using Autoencoders to Classify EMC Problems in Electronic System Development

J. Maalouly, D. Hemker, C. Hedayat, M. Olbrich, S. Lange, H. Mathis, Advances in Radio Science 22 (2024) 53–59.

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

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