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dc.contributor.authorBilík, Šimon
dc.date.accessioned2021-07-15T11:17:22Z
dc.date.available2021-07-15T11:17:22Z
dc.date.issued2020cs
dc.identifier.citationProceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 351-355. ISBN 978-80-214-5867-3cs
dc.identifier.isbn978-80-214-5867-3
dc.identifier.urihttp://hdl.handle.net/11012/200594
dc.description.abstractThis article brings an overview of the bee monitoring methods and is divided into two parts. The first part, which covers the general monitoring methods, describes the methods based on the sensor fusion data and acoustic measurements and the second part focuses on computer vision methods based applications for the Varroa Destructor mite detection. The conclusion drafts possible extension of those methods with the use of the deep learning methods and also the future direction of the author’s research.en
dc.formattextcs
dc.format.extent351-355cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 26st Conference STUDENT EEICT 2020: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/EEICT2020cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.subjectHoney bee monitoringen
dc.subjectVarroa Destructoren
dc.subjectMachine intelligenceen
dc.titleHoney Bee (APIS Mellifera) Colony Monitoring Methods With A Potential Application Of The Machine Intelligence Methodsen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date23.04.2020cs
but.event.titleStudent EEICT 2020cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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