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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. The Editors 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.
Machine learning. --- Cooperating objects (Computer systems) --- Learning, Machine --- Artificial intelligence --- Machine theory --- Engineering. --- Computer network architectures. --- Telecommunication. --- Data mining. --- Computational Intelligence. --- Computer Systems Organization and Communication Networks. --- Communications Engineering, Networks. --- Data Mining and Knowledge Discovery. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- Construction --- Industrial arts --- Technology --- Computational intelligence. --- Computer organization. --- Electrical engineering. --- Electric engineering --- Engineering --- Organization, Computer --- Electronic digital computers --- Intelligence, Computational --- Soft computing
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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. The Editors 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.
Electrical engineering --- Applied physical engineering --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- computers --- KI (kunstmatige intelligentie) --- elektrotechniek --- data acquisition --- AI (artificiële intelligentie)
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Electrical engineering --- Applied physical engineering --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- computers --- KI (kunstmatige intelligentie) --- elektrotechniek --- data acquisition
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