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vls/2603noah-balancer_mdapi1elekpub.bib.uni-wuppertal.devdPrediction rating and performance improvement for segmentation networks by time-dynamic uncertainty estimatesMaag, KiraVerfasserautBergische Universität WuppertalGrad-verleihende InstitutiondggtextthesisTextHochschulschriftthesisdoctoralThesisgwXA-DEWuppertal03.08.20212021single unitengelectronic resourceremote1 Online-Ressource (VII, 140 Seiten) Illustrationen, DiagrammeComputerOnline-Ressourceeingereicht von Kira Maag, M. Sc.Bergische Universität Wuppertal, Dissertation, 2021Wuppertalurn:nbn:de:hbz:468-20211007-111502-810.25926/jtyb-cd3499371063704406441Prediction rating and performance improvement for segmentation networks by time-dynamic uncertainty estimatesMaag, KiraDruck-AusgabeHT021095272https://doi.org/10.25926/jtyb-cd34http://nbn-resolving.de/urn/resolver.pl?urn=urn%3Anbn%3Ade%3Ahbz%3A468-20211007-111502-8http://elpub.bib.uni-wuppertal.de/edocs/dokumente/fbc/mathematik/diss2021/maag/Open AccessRS INC 1.0oaDoctoralThesispublicrda21111820231126163413.0HT021151505ger510 https://elekpub.bib.uni-wuppertal.de//domainresource/static/graphics/connectors/viewerLogo.gifWuppertal : Bergische Universität Wuppertalreserved https://ub-wuppertal.digibib.net/search/katalog/record/(DE-605)HT021151505 https://elekpub.bib.uni-wuppertal.de/id/6249466 https://elekpub.bib.uni-wuppertal.de/i3f/v20/6249466/manifest https://elekpub.bib.uni-wuppertal.de/proto_ftsearch/6249466