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.
Nowadays machines can learn und develop self maintaining procedures, meaning that those systems can provide a broad range of substantial improvements if introduced in production. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis.
The 5th Conference on Machine Learning for Cyber Physical Systems and Industry 4.0 - ML4CPS - addresses these topics.
Main topics of the conference are:
Machine Learning Methods – Deep Learning
Smart Data – Semantics and Meta Data
Machine Learning for Security
Ehtics of Machine Learning
Machine Learning in Robotics
Business Models for Machine Learning
Machine Learning on the Edge
The conference offers a forum to present new approaches to Machine Learning for Cyber Physical Systems, to discuss experiences and to develop visions. Therefore, the conference addresses researchers and users from different industry sectors such as production technology, automation, automotive and telecommunication.
Professor Dr.-Ing. habil. Jürgen Beyerer, Fraunhofer Institut IOSB
Professor Dr. rer. nat. Oliver Niggemann, Institut für Automatisierungstechnik, Helmut-Schmidt Universität / Universität der Bundeswehr Hamburg
For more information and registration to the conference please contact