Editors:
- Includes the full proceedings of the 2017 ML4CPS – Machine Learning for Cyber Physical Systems Conference
- Presents recent and new advances in automated machine learning methods
- Provides an accessible and succinct overview on machine learning for cyber physical systems
Part of the book series: Technologien für die intelligente Automation (TIA, volume 11)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (10 papers)
-
Front Matter
About this book
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 25th-26th, 2017.
Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Editors and Affiliations
-
Institut für Optronik, Systemtechnik und Bildauswertung, Fraunhofer, Karlsruhe, Germany
Jürgen Beyerer
-
Industrial Automation, Fraunhofer-Anwendungszentrum, Lemgo, Germany
Alexander Maier
-
inIT - Institut für industrielle Informationstechnik, Hochschule Ostwestfalen-Lippe, Lemgo, Germany
Oliver Niggemann
About the editors
Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.
Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on the development of algorithms for big data applications in Cyber-Physical Systems (diagnostics, optimization, predictive maintenance) and the transfer of research results to industry.
Prof. Dr. Oliver Niggemann is Professor for Artificial Intelligence in Automation. His research interests are in the fields of machine learning and data analysis for Cyber-Physical Systems and in the fields of planning and diagnosis of distributed systems. He is a board member of the research institute inIT and deputy director at the Fraunhofer Application Center Industrial Automation INA located in Lemgo.
Bibliographic Information
Book Title: Machine Learning for Cyber Physical Systems
Book Subtitle: Selected papers from the International Conference ML4CPS 2017
Editors: Jürgen Beyerer, Alexander Maier, Oliver Niggemann
Series Title: Technologien für die intelligente Automation
DOI: https://doi.org/10.1007/978-3-662-59084-3
Publisher: Springer Vieweg Berlin, Heidelberg
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer-Verlag GmbH Germany, part of Springer Nature 2020
Softcover ISBN: 978-3-662-59083-6Published: 10 April 2019
eBook ISBN: 978-3-662-59084-3Published: 09 April 2019
Series ISSN: 2522-8579
Series E-ISSN: 2522-8587
Edition Number: 1
Number of Pages: VII, 87
Number of Illustrations: 1 b/w illustrations
Topics: Computational Intelligence, Computer Systems Organization and Communication Networks, Communications Engineering, Networks, Data Mining and Knowledge Discovery