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Machine Learning for Cyber Physical Systems

Selected papers from the International Conference ML4CPS 2017

Technologien für die intelligente Automation Band 11

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Beschreibung


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.




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.



Produktdetails

Einband Taschenbuch
Herausgeber Jürgen Beyerer, Alexander Maier, Oliver Niggemann
Seitenzahl 87
Erscheinungsdatum 10.04.2019
Sprache Englisch
ISBN 978-3-662-59083-6
Verlag Springer Berlin
Maße (L/B/H) 24/16,8/0,5 cm
Gewicht 180 g
Abbildungen 9 schwarz-weiße und 33 farbige Abbildungen, Bibliographie
Auflage 1st ed. 2020

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