Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-2758
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dc.contributor.authorMichau, Gabriel-
dc.contributor.authorThomas, Palmé-
dc.contributor.authorFink, Olga-
dc.date.accessioned2018-12-19T10:22:49Z-
dc.date.available2018-12-19T10:22:49Z-
dc.date.issued2017-
dc.identifier.isbn978-1-936263-26-4de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13981-
dc.language.isoende_CH
dc.publisherPHM Societyde_CH
dc.rightshttp://creativecommons.org/licenses/by/3.0/de_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleDeep feature learning network for fault detection and isolationde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
dc.identifier.doi10.21256/zhaw-2758-
zhaw.conference.detailsPHM 2017, St. Petersburg, USA, 2-5 October 2017de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end118de_CH
zhaw.pages.start108de_CH
zhaw.parentwork.editorBregon, Anibal-
zhaw.parentwork.editorDaigle, Matthew J.-
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewNot specifiedde_CH
zhaw.title.proceedingsPHM 2017 : Proceedings of the Annual Conference of the Prognostics and Health Management Society 2017de_CH
Appears in Collections:Publikationen School of Engineering

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