Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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Machine Learning for Cyber Physical Systems. Selected papers from the International Conference ML4CPS 2018

2019 , Beyerer, Jürgen , Kühnert, Christian , Niggemann, Oliver

This Open Access proceedings 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 Karlsruhe, October 23-24, 2018. 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.

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ML4CPS 2015, 1st Conference on Machine Learning for Cyber Physical Systems and Industry 4.0. CD-ROM

2015 , Niggemann, Oliver , Beyerer, Jürgen

Die erste Konferenz ML4CPS- Machine Learning for Cyber Physical Systems and Industry 4.0 widmet sich nun genau diesem Themenfeld. Die zweitägige Veranstaltung bildet ein Forum, um neue Ansätze zum maschinellen Lernen für cyber-physische Systeme zu präsentieren, Erfahrungen auszutauschen, zu diskutieren und Visionen zu entwickeln. Dazu adressiert die Konferenz Forscher und Anwender aus unterschiedlichen Branchen wie der Produktionstechnik, Automatisierung, Automotive und Telekommunikation.

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Publication

Machine Learning for Cyber Physical Systems

2017 , Beyerer, Jürgen , Niggemann, Oliver , Kühnert, Christian

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 Karlsruhe, September 29th, 2016. 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.

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Publication

Machine Learning for Cyber Physical Systems

2016 , Niggemann, Oliver , Beyerer, Jürgen

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.

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