| SMSI 2023 |
A1.3 - Digital Transformation of Processing Metrological Services |
C. Kulka-Peschke, S. Eickelberg, A. Keidel, M. Meiborg, A. Oppermann - Physikalisch-Technische Bundesanstalt (PTB), Berlin (Germany) |
| SMSI 2023 |
A1.4 - A Cloud Native Architecture for automated Metrological Services |
A. Oppermann, S. Eickelberg, A. Keidel, C. Kulka-Peschke, M. Meiborg - Physikalisch-Technische Bundesanstalt, Berlin (Germany) |
| SMSI 2023 |
PT4 - Metrology for Climate Observation: European Coordination |
E. Wooliams, N. Fox - National Physical Laboratory, Teddington (United Kingdom), C. Pascale - Federal Institute of Metrology (METAS), Bern-Wabern (Switzerland), P. Fisicaro - Laboratoire national de métrologie et d’essais (LNE), Paris (France) |
| SMSI 2023 |
A2.1 - NDE Sensors for Traceability by Material Fingerprints |
K. Jacob - Fraunhofer Institute for Nondestructive Testing IZFP, Saarbrücken (Germany) |
| SMSI 2023 |
A2.2 - Non-destructive inline sensors for digital material twin in the carbon fiber tape laying process |
J. Oswald, J. Summa, C. Jungmann, D. Koster, U. Rabe - Fraunhofer Institute for Nondestructive Testing IZFP, Saarbrücken (Germany) |
| SMSI 2023 |
A2.3 - Information recycling of NDE data sets |
F. Leinenbach, B. Sprau, C. Stumm - Fraunhofer IZFP, Saarbrücken (Germany) |
| SMSI 2023 |
A2.4 - Deep Learning-Assisted Optimal Sensor Placement in Ultrasound NDT |
H. Wang, E. Pérez, F. Römer - Fraunhofer IZFP, Saarbrücken (Germany) |
| SMSI 2023 |
A3.1 - Making AI Measureable - Approaches within the “Metrology for Artificial Intelligence in Medicine Programme” of PTB |
H. Rabus - Physikalisch-Technische Bundesanstalt, Berlin (Germany) |
| SMSI 2023 |
A3.2 - Co-Calibration in Distributed Homogeneous Sensor Networks |
M. Gruber, S. Eichstädt, A. Vedurmudi - Physikalisch-Technische Bundesanstalt, Berlin (Germany) |
| SMSI 2023 |
A3.3 Active Display Registration in Phase Measuring Deflectometry |
Y. Sperling, R. Bergmann - Bremer Institut für angewandte Strahltechnik, Bremen (Germany) |
