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dc.creatorCamuñas Mesa, Luis Alejandroes
dc.creatorZamarreño Ramos, Carloses
dc.creatorLinares Barranco, Alejandroes
dc.creatorAcosta Jiménez, Antonio Josées
dc.creatorSerrano Gotarredona, María Teresaes
dc.creatorLinares Barranco, Bernabées
dc.date.accessioned2020-02-13T11:15:05Z
dc.date.available2020-02-13T11:15:05Z
dc.date.issued2012
dc.identifier.citationCamuñas Mesa, L.A., Zamarreño Ramos, C., Linares Barranco, A., Acosta Jiménez, A.J., Serrano Gotarredona, M.T. y Linares Barranco, B. (2012). An Event-Driven Multi-Kernel Convolution Processor Module for Event-Driven Vision Sensors. IEEE Journal of Solid-State Circuits, 47 (2), 504-517.
dc.identifier.issn0018-9200es
dc.identifier.urihttps://hdl.handle.net/11441/93004
dc.description.abstractEvent-Driven vision sensing is a new way of sensing visual reality in a frame-free manner. This is, the vision sensor (camera) is not capturing a sequence of still frames, as in conventional video and computer vision systems. In Event-Driven sensors each pixel autonomously and asynchronously decides when to send its address out. This way, the sensor output is a continuous stream of address events representing reality dynamically continuously and without constraining to frames. In this paper we present an Event-Driven Convolution Module for computing 2D convolutions on such event streams. The Convolution Module has been designed to assemble many of them for building modular and hierarchical Convolutional Neural Networks for robust shape and pose invariant object recognition. The Convolution Module has multi-kernel capability. This is, it will select the convolution kernel depending on the origin of the event. A proof-of-concept test prototype has been fabricated in a 0.35 m CMOS process and extensive experimental results are provided. The Convolution Processor has also been combined with an Event-Driven Dynamic Vision Sensor (DVS) for high-speed recognition examples. The chip can discriminate propellers rotating at 2 k revolutions per second, detect symbols on a 52 card deck when browsing all cards in 410 ms, or detect and follow the center of a phosphor oscilloscope trace rotating at 5 KHz.es
dc.description.sponsorshipUnión Europea 216777 (NABAB)es
dc.description.sponsorshipMinisterio de Ciencia e Innovación TEC2009-10639-C04-01es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofIEEE Journal of Solid-State Circuits, 47 (2), 504-517.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAddress event representation (AER)es
dc.subjectAsynchronous vision sensors and processorses
dc.subjectHigh-speed imaginges
dc.subjectImage convolutionses
dc.subjectImage sensorses
dc.subjectMachine visiones
dc.subjectNeural networks hardwarees
dc.subjectNeuromorphic circuitses
dc.subjectRobot vision systemses
dc.subjectVisual systemes
dc.titleAn Event-Driven Multi-Kernel Convolution Processor Module for Event-Driven Vision Sensorses
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadoreses
dc.relation.projectID216777 (NABAB)es
dc.relation.projectIDTEC2009-10639-C04-01es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/6054033es
dc.identifier.doi10.1109/JSSC.2011.2167409es
dc.contributor.groupUniversidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitaciónes
idus.format.extent13es
dc.journaltitleIEEE Journal of Solid-State Circuitses
dc.publication.volumen47es
dc.publication.issue2es
dc.publication.initialPage504es
dc.publication.endPage517es
dc.identifier.sisius20099989es

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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as: Attribution-NonCommercial-NoDerivatives 4.0 Internacional