Measurement systems and sensors with cognitive features
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Klaus-Dieter Sommer
Klaus-Dieter Sommer is an Honorary Professor at the Technische Universität Ilmenau, the Technische Universität Braunschweig, and the Friedrich-Alexander University of Erlangen-Nuremberg. He is Chairperson of the VDI-VDE-GMA Expert Advisory Board “Fundamentals and Methods of Measurement and Automation”, and General Co-Chair of the SMSI 2023 Conference.
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Michael Heizmann
Michael Heizmann is a Full Professor of Mechatronic Measurement Systems and Director of the Institute of Industrial Information Technology, Karlsruhe Institute of Technology. His research interests include measurement and automation technology, and their applications. He is Chairperson of the VDI-VDE-GMA Expert Advisory Board “Optical Technologies” and member of the Steering Committee of the VDI-VDE-GMA.
Andreas Schütze is a full professor for Measurement Technology in the Department Systems Engineering at Saarland University, Saarbrücken, Germany and head of the Laboratory for Measurement Technology (LMT). His research interests include smart gas sensor systems as well as data engineering methods for industrial applications.
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Editorial
- Measurement systems and sensors with cognitive features
- Beiträge
- The digital transformation and novel calibration approaches
- Comparison of different ML methods concerning prediction quality, domain adaptation and robustness
- Assessment of quality predictions achieved with machine learning using established measurement process capability procedures in manufacturing
- Cognitive sensor systems for NDE 4.0: Technology, AI embedding, validation and qualification
- GAN-regularized augmentation strategy for spectral datasets
- Automatic multimodal sensor calibration of the UNICARagil vehicles
Artikel in diesem Heft
- Frontmatter
- Editorial
- Measurement systems and sensors with cognitive features
- Beiträge
- The digital transformation and novel calibration approaches
- Comparison of different ML methods concerning prediction quality, domain adaptation and robustness
- Assessment of quality predictions achieved with machine learning using established measurement process capability procedures in manufacturing
- Cognitive sensor systems for NDE 4.0: Technology, AI embedding, validation and qualification
- GAN-regularized augmentation strategy for spectral datasets
- Automatic multimodal sensor calibration of the UNICARagil vehicles
