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dc.creatorSerrano Gotarredona, María Teresaes
dc.creatorLinares Barranco, Bernabées
dc.date.accessioned2018-05-07T14:32:48Z
dc.date.available2018-05-07T14:32:48Z
dc.date.issued2015
dc.identifier.citationSerrano Gotarredona, M.T. y Linares Barranco, B. (2015). Poker-DVS and MNIST-DVS. Their History, How They Were Made, and Other Details. Frontiers in Neuroscience, 9, 481-.
dc.identifier.issn1662-4548es
dc.identifier.issn1662-453Xes
dc.identifier.urihttps://hdl.handle.net/11441/74214
dc.description.abstractThis article reports on two databases for event-driven object recognition using a Dynamic Vision Sensor (DVS). The first, which we call Poker-DVS and is being released together with this article, was obtained by browsing specially made poker card decks in front of a DVS camera for 2–4 s. Each card appeared on the screen for about 20–30 ms. The poker pips were tracked and isolated off-line to constitute the 131-recording Poker-DVS database. The second database, which we call MNIST-DVS and which was released in December 2013, consists of a set of 30,000 DVS camera recordings obtained by displaying 10,000 moving symbols from the standard MNIST 70,000-picture database on an LCD monitor for about 2–3 s each. Each of the 10,000 symbols was displayed at three different scales, so that event-driven object recognition algorithms could easily be tested for different object sizes. This article tells the story behind both databases, covering, among other aspects, details of how they work and the reasons for their creation. We provide not only the databases with corresponding scripts, but also the scripts and data used to generate the figures shown in this article (as Supplementary Material).es
dc.description.sponsorshipJunta de Andalucía TIC-6091es
dc.description.sponsorshipMinisterio de Economía y Competitividad TEC2012-37868-C04-01es
dc.description.sponsorshipEuropean Union FP7-604102, H2020-644096es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherFrontiers Mediaes
dc.relation.ispartofFrontiers in Neuroscience, 9, 481-.
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Estados Unidos de América*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEvent-driven visiones
dc.subjectEvent-driven object recognitiones
dc.subjectDynamic vision sensor (DVS)es
dc.subjectAddress event representationes
dc.subjectHigh speed visiones
dc.subjectFrame-free visiones
dc.titlePoker-DVS and MNIST-DVS. Their History, How They Were Made, and Other Detailses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadoreses
dc.relation.projectIDTIC-6091es
dc.relation.projectIDTEC2012-37868-C04-01es
dc.relation.projectIDFP7-604102es
dc.relation.projectIDH2020-644096es
dc.relation.publisherversionhttp://dx.doi.org/10.3389/fnins.2015.00481es
dc.identifier.doi10.3389/fnins.2015.00481es
idus.format.extent10 p.es
dc.journaltitleFrontiers in Neurosciencees
dc.publication.volumen9es
dc.publication.initialPage481es

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