Data-driven classification of events in the vicinity of an optical fibre

dc.contributor.author	Galaz, Zoltan
dc.contributor.author	Mekyska, Jiri
dc.contributor.author	Prinosil, Jiri
dc.contributor.author	Novotny, Vit
dc.coverage.issue	2	cs
dc.coverage.volume	23	cs
dc.date.accessioned	2023-10-09T07:00:37Z
dc.date.available	2023-10-09T07:00:37Z
dc.date.issued	2021-06-29	cs
dc.description.abstract	This article focuses on the data-driven classification of vibration sources via a distributed optical fibre sensor system utilizing Gaussian Mixture Models and Mel-spectrograms. In total, six categories are considered: one person walking/running, group walking/running, hammering, and car riding. Two evaluation scenarios are used: individual models (per-session) and a joint model. Tenfold cross-validation is employed during the evaluation phase.	en
dc.format	text	cs
dc.format.extent	43-48	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Elektrorevue. 2021, vol. 23, č. 2, s. 43-48. ISSN 1213-1539	cs
dc.identifier.issn	1213-1539
dc.identifier.uri	http://hdl.handle.net/11012/214145
dc.language.iso	en	cs
dc.publisher	International Society for Science and Engineering, o.s.	cs
dc.relation.ispartof	Elektrorevue	cs
dc.relation.uri	http://www.elektrorevue.cz/	cs
dc.rights	(C) 2021 Elektrorevue	en
dc.rights.access	openAccess	en
dc.title	Data-driven classification of events in the vicinity of an optical fibre	en
dc.type.driver	article	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en
eprints.affiliatedInstitution.faculty	Fakulta elektrotechniky a komunikačních technologií	cs

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