• Produktbild: Machine Learning for Cyber Physical Systems
  • Produktbild: Machine Learning for Cyber Physical Systems
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Machine Learning for Cyber Physical Systems Selected papers from the International Conference ML4CPS 2017

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

10.04.2019

Abbildungen

VII, 87 p. 1 illus.

Herausgeber

Jürgen Beyerer + weitere

Verlag

Springer Berlin

Seitenzahl

87

Maße (L/B/H)

24/16,8/0,6 cm

Gewicht

177 g

Auflage

1st edition 2020

Sprache

Englisch

ISBN

978-3-662-59083-6

Beschreibung

Portrait

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

Erscheinungsdatum

10.04.2019

Abbildungen

VII, 87 p. 1 illus.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

87

Maße (L/B/H)

24/16,8/0,6 cm

Gewicht

177 g

Auflage

1st edition 2020

Sprache

Englisch

ISBN

978-3-662-59083-6

Herstelleradresse

Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

Email: GPSR Kontakt

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  • Produktbild: Machine Learning for Cyber Physical Systems
  • Produktbild: Machine Learning for Cyber Physical Systems
  • Prescriptive Maintenance of CPPS by Integrating Multi-modal Data with Dynamic Bayesian Networks.- Evaluation of Deep Autoencoders for Prediction of Adjustment Points in the Mass Production of Sensors.- Differential Evolution in Production Process Optimization of Cyber Physical Systems.- Machine Learning for Process-X: A Taxonomy.- Intelligent edge processing.- Learned Abstraction: Knowledge Based Concept Learning for Cyber Physical Systems.- Semi-supervised Case-based Reasoning Approach to Alarm Flood Analysis.- Verstehen von Maschinenverhalten mit Hilfe von Machine Learning.- Adaptable Realization of Industrial Analytics Functions on Edge-Devices using Recongurable Architectures.- The Acoustic Test System for Transmissions in the VW Group.