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dc.contributor.editorNiggemann, Oliver
dc.contributor.editorBeyerer, Jürgen
dc.contributor.editorKrantz, Maria
dc.contributor.editorKühnert, Christian
dc.date.accessioned2024-07-16T18:50:15Z
dc.date.available2024-07-16T18:50:15Z
dc.date.issued2024
dc.identifierONIX_20240716_9783031470622_2
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/92296
dc.description.abstractThis 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 Hamburg (Germany), March 29th to 31st, 2023. 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. This is an open access book.
dc.languageEnglish
dc.relation.ispartofseriesTechnologien für die intelligente Automation
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general::GPF Information theory::GPFC Cybernetics and systems theory
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UK Computer hardware
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PB Mathematics::PBW Applied mathematics::PBWH Mathematical modelling
dc.subject.otherCyber-physical systems
dc.subject.otherNeural networks
dc.subject.otherComputer Science
dc.subject.otherNetwork architecture
dc.subject.otherAutomatic validation
dc.subject.otherMachine learning
dc.titleMachine Learning for Cyber-Physical Systems
dc.title.alternativeSelected papers from the International Conference ML4CPS 2023
dc.typebook
oapen.identifier.doi10.1007/978-3-031-47062-2
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.relation.isFundedByc7199471-8126-48cd-bade-e00fd8cb43ec
oapen.relation.isbn9783031470622
oapen.relation.isbn9783031470615
oapen.imprintSpringer Nature Switzerland
oapen.series.number18
oapen.pages129
oapen.place.publicationCham
oapen.grant.number[...]


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