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dc.date.accessioned 2020-09-16T16:19:01Z
dc.date.available 2020-09-16T16:19:01Z
dc.date.issued 2020
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/104768
dc.description.abstract In massive biometric identification, response times highlydepend on the searching algorithms. Traditional systems operate with databases of up to 10,000 records. In large databases, with an increasing number of simultaneous queries, the system response time is a critical factor. This work proposes a GPU-based implementation for the matching process of finger-vein massive identification. Experimental resultss how that our approach solves up to 256 simultaneous queries on large databases achieving up to 136x. en
dc.language en es
dc.subject High Performance Computing es
dc.subject Identification of individuals es
dc.subject Local linear binary pattern es
dc.subject Finger veins es
dc.subject GPU es
dc.title Finger-vein individuals identification on massive databases en
dc.type Objeto de conferencia es
sedici.identifier.isbn 978-950-34-1927-4 es
sedici.creator.person Guidet, Sebastián es
sedici.creator.person Barrientos, Ricardo J. es
sedici.creator.person Frati, Fernando Emmanuel es
sedici.creator.person Hernández-García, Ruber es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Instituto de Investigación en Informática es
mods.originInfo.place Instituto de Investigación en Informática es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.date.exposure 2020-09
sedici.relation.event VIII Conference on Cloud Computing, Big Data & Emerging Topics (Modalidad virtual, 8 al 10 de septiembre de 2020) es
sedici.description.peerReview peer-review es
sedici.relation.isRelatedWith http://sedici.unlp.edu.ar/handle/10915/103585 es
sedici.relation.isRelatedWith http://sedici.unlp.edu.ar/handle/10915/103585 es
sedici.relation.bookTitle Short Papers of the 8th Conference on Cloud Computing Conference, Big Data & Emerging Topics (JCC-BD&ET 2020) es


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)