Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106935
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dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.contributorPhotonics Research Centreen_US
dc.creatorWang, Ben_US
dc.creatorGuo, Nen_US
dc.creatorWang, Len_US
dc.creatorYu, Cen_US
dc.creatorLu, Cen_US
dc.date.accessioned2024-06-07T00:58:58Z-
dc.date.available2024-06-07T00:58:58Z-
dc.identifier.isbn978-1-943580-50-7en_US
dc.identifier.urihttp://hdl.handle.net/10397/106935-
dc.descriptionOptical Fiber Sensors 2018, Lausanne Switzerland, 24-28 September 2018en_US
dc.language.isoenen_US
dc.publisherOptica Publishing Groupen_US
dc.rights© 2018 The Author(s)en_US
dc.rightsThe following publication B. Wang, N. Guo, L. Wang, C. Yu, and C. Lu, "Denoising and Robust Temperature Extraction for BOTDA Systems based on Denoising Autoencoder and DNN," in 26th International Conference on Optical Fiber Sensors, OSA Technical Digest (Optica Publishing Group, 2018), paper WF29 is available at https://doi.org/10.1364/OFS.2018.WF29.en_US
dc.titleDenoising and robust temperature extraction for BOTDA systems based on denoising autoencoder and DNNen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1364/ofs.2018.wf29en_US
dcterms.abstractDenoising autoencoder is used for denoising of the data obtained by the Brillouin optical time-domain analyzer (BOTDA) sensing system and is also used to form the deep neural networks (DNN) for robust temperature information extraction.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitation26th International Conference on Optical Fiber Sensors, OSA Technical Digest (Optica Publishing Group, 2018), paper WF29en_US
dcterms.issued2018-
dc.identifier.scopus2-s2.0-85059467556-
dc.relation.conferenceOptical Fiber Sensors [OFS]en_US
dc.identifier.artnWF29en_US
dc.description.validate202405 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberEIE-0467-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHKPU grant; Project of Strategic Importanceen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS20010967-
dc.description.oaCategoryVoR alloweden_US
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