A Heterogenous and Reconfigurable Embedded Architecture for Energy-Efficient Execution of Convolutional Neural Networks

dc.contributor.author	Lübeck, Konstantin
dc.contributor.author	Bringmann, Oliver
dc.date.accessioned	2020-05-25T14:07:09Z
dc.date.available	2020-05-25T14:07:09Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/10900/100908
dc.language.iso	en	de_DE
dc.publisher	Cham: Springer	de_DE
dc.relation.ispartofseries	Lecture notes in computer science;11479
dc.relation.uri	http://dx.doi.org/10.1007/978-3-030-18656-2_20	de_DE
dc.subject.ddc	004	de_DE
dc.title	A Heterogenous and Reconfigurable Embedded Architecture for Energy-Efficient Execution of Convolutional Neural Networks	de_DE
dc.type	BookPart	de_DE
dc.type	ConferenceObject	de_DE
utue.publikation.seiten	267-280	de_DE
utue.personen.roh	Lübeck, Konstantin
utue.personen.roh	Bringmann, Oliver
utue.publikation.buchdesbeitrags	Schoeberl M., Hochberger C., Uhrig S., Brehm J., Pionteck T. (eds) Architecture of Computing Systems – ARCS 2019	de_DE