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dc.contributor.authorLordelo, Cen_US
dc.contributor.authorBenetos, Een_US
dc.contributor.authorDixon, Sen_US
dc.contributor.authorAhlback, Sen_US
dc.contributor.authorIEEEen_US
dc.date.accessioned2019-08-13T10:49:58Z
dc.date.available2019-07-15en_US
dc.date.issued2019en_US
dc.identifier.issn1931-1168en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/59067
dc.format.extent40 - 44en_US
dc.subjectHarmonic-percussive source separationen_US
dc.subjectDenseNeten_US
dc.subjectMDenseNeten_US
dc.subjectkernel shapesen_US
dc.subjectdeep learningen_US
dc.subjectmusic separationen_US
dc.titleINVESTIGATING KERNEL SHAPES AND SKIP CONNECTIONS FOR DEEP LEARNING-BASED HARMONIC-PERCUSSIVE SEPARATIONen_US
dc.typeConference Proceeding
dc.rights.holder© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
pubs.author-urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000527800200009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6aen_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US


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