Hybrid Edge-Cloud Models for Bearing Failure Detection in a Fleet of Machines

dc.contributor.author	Leroux, Sam
dc.contributor.author	Simoens, Pieter
dc.contributor.imecauthor	Leroux, Sam
dc.contributor.imecauthor	Simoens, Pieter
dc.contributor.orcidimec	Leroux, Sam::0000-0003-3792-5026
dc.contributor.orcidimec	Simoens, Pieter::0000-0002-9569-9373
dc.date.accessioned	2025-02-05T10:16:36Z
dc.date.available	2025-01-06T16:50:16Z
dc.date.available	2025-01-07T10:15:35Z
dc.date.available	2025-02-05T10:16:36Z
dc.date.embargo	2024-12-31
dc.date.issued	2024
dc.description.wosFundingText	This research received funding from the Flemish Government under the "Onderzoeksprogramma Artificiele Intelligentie (AI) Vlaanderen" program.
dc.identifier.doi	10.3390/electronics13245034
dc.identifier.issn	2079-9292
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/45044
dc.publisher	MDPI
dc.source.beginpage	Art. 5034
dc.source.endpage	N/A
dc.source.issue	24
dc.source.journal	ELECTRONICS
dc.source.numberofpages	17
dc.source.volume	13
dc.subject.keywords	FAULT-DIAGNOSIS
dc.title	Hybrid Edge-Cloud Models for Bearing Failure Detection in a Fleet of Machines
dc.type	Journal article
dspace.entity.type	Publication
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