Machine Learning for Cyber Physical Systems: Selected papers from the International Conference ML4CPS 2015 - Brossura

Brossura

ISBN 10: 3662488361 ISBN 13: 9783662488362

Casa editrice: Springer Vieweg, 2016

Riassunto

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 1-2, 2015.

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.

Su questo libro

Informazioni sull?autore

Prof. Dr. Oliver Niggemann ist seit November 2008 Mitglied des inIT. Er vertritt das Fachgebiet Embedded Software Engineering in der Lehre und forscht im inIT in den Bereichen Verteilte Echtzeit-Software und der Analyse und Diagnose verteilter Systeme. Gleichzeitig forscht Prof. Niggemann im Fraunhofer-Anwendungszentrum Industrial Automation (INA) in Lemgo.

Prof. Dr.-Ing. Jürgen Beyerer ist in Personalunion Inhaber des Lehrstuhls für Interaktive Echtzeitsysteme an der Fakultät für Informatik und Leiter des Fraunhofer IOSB. Die Schwerpunkte in Forschung und Lehre am Lehrstuhl für Interaktive Echtzeitsysteme liegen auf den Themen: automatische Sichtprüfung und Bildauswertung, Mustererkennung und Signal- und Informationsverarbeitung.

Dalla quarta di copertina

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 1-2, 2015.

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.

Dettagli dell'edizione

• Editore: Springer Vieweg
• Data di pubblicazione: 2016
• Lingua: Inglese
• ISBN 10: 3662488361
• ISBN 13: 9783662488362
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 128
• Redattore: Niggemann Oliver, Beyerer Jürgen
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania