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dc.contributor.authorBecker, Daniel*
dc.date.accessioned2021-02-12T00:56:52Z
dc.date.available2021-02-12T00:56:52Z
dc.date.issued2017*
dc.date.submitted2019-07-30 20:02:00*
dc.identifier35018*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/57700
dc.description.abstractIn photon science more and more data are taken. It is not possible anymore to store and process all data offline. In this book, we explore strategies for handling this large amount of data. A neural network as well as techniques from image processing are used to efficiently categorize and select useful data. We also indicate why many sophisticated algorithms cannot be used in this context. In addition, a prototype for data selection is presented, discussed, and benchmarked.*
dc.languageEnglish*
dc.subjectQA75.5-76.95*
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer scienceen_US
dc.subject.othernanocrystalligraphy*
dc.subject.otherimage-processing*
dc.subject.othersignalverarbeitungbig data*
dc.subject.othersignal-processing*
dc.subject.othernanokristallographie*
dc.subject.otherechtzeitverarbeitung*
dc.subject.otherreal-time-processing*
dc.subject.otherbig data*
dc.subject.otherbildverarbeitung*
dc.titleRealtime Analysis of Large-Scale Data*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000056498*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731505525*
oapen.pagesXIII, 98 p.*
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityScientific or Editorial Board
peerreview.id8ad5c235-9810-49eb-b358-27c8675324d9
peerreview.titleDissertations (Dissertationen)


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