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Machine Learning for Cyber Physical Systems - Selected papers from the International Conference ML4CPS 2018 (Paperback, 1st ed. 2019) Loot Price: R1,589
Discovery Miles 15 890
Repayment Terms: R149 pm x 12*
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Machine Learning for Cyber Physical Systems - Selected papers from the International Conference ML4CPS 2018 (Paperback, 1st ed....

Machine Learning for Cyber Physical Systems - Selected papers from the International Conference ML4CPS 2018 (Paperback, 1st ed. 2019)

Jurgen Beyerer, Christian Kuhnert, Oliver Niggemann

Series: Technologien fur die intelligente Automation, 9

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Loot Price R1,589 Discovery Miles 15 890 | Repayment Terms: R149 pm x 12*

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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.

General

Imprint: Springer Vieweg
Country of origin: Germany
Series: Technologien fur die intelligente Automation, 9
Release date: December 2018
First published: 2019
Editors: Jurgen Beyerer • Christian Kuhnert • Oliver Niggemann
Dimensions: 240 x 168mm (L x W)
Format: Paperback
Pages: 136
Edition: 1st ed. 2019
ISBN-13: 978-3-662-58484-2
Categories: Books > Computing & IT > Computer communications & networking > General
Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General
Books > Computing & IT > Applications of computing > Databases > Data mining
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-662-58484-0
Barcode: 9783662584842

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