Fully-convolutional denoising auto-encoders for NILM in large non-residential buildings

dc.contributor.author	García Pérez, Diego
dc.contributor.author	Pérez López, Daniel
dc.contributor.author	Díaz Blanco, Ignacio
dc.contributor.author	González Muñiz, Ana
dc.contributor.author	Domínguez González, Manuel
dc.contributor.author	Cuadrado Vega, Abel Alberto
dc.date.accessioned	2021-07-26T07:50:35Z
dc.date.available	2021-07-26T07:50:35Z
dc.date.issued	2021
dc.identifier.citation	IEEE Transactions on Smart Grid, 12(3), p. 2722-2731 (2021); doi:10.1109/TSG.2020.3047712
dc.identifier.issn	1949-3053
dc.identifier.uri	http://hdl.handle.net/10651/60026
dc.description.sponsorship	Principado de Asturias Government through the Predoctoral Grant "Severo Ochoa''.
dc.format.extent	p. 2722-2731
dc.language.iso	eng
dc.relation.ispartof	IEEE Transactions on Smart Grid
dc.rights	© 2020 IEEE
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099087289&doi=10.1109%2fTSG.2020.3047712&partnerID=40&md5=3de9b98c830097ee3f4a848db27d3a72
dc.title	Fully-convolutional denoising auto-encoders for NILM in large non-residential buildings
dc.type	journal article
dc.identifier.doi	10.1109/TSG.2020.3047712
dc.relation.publisherversion	http://dx.doi.org/10.1109/TSG.2020.3047712

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