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Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/127428
DC FieldValueLanguage
dc.contributor.authorFaundez-Zanuy, Marcosen_US
dc.contributor.authorDíaz Cabrera, Moisésen_US
dc.date.accessioned2023-10-30T14:10:10Z-
dc.date.available2023-10-30T14:10:10Z-
dc.date.issued2023en_US
dc.identifier.isbn9783031430848en_US
dc.identifier.issn0302-9743en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/127428-
dc.description.abstractThis paper investigates the impact of different approximation methods in feature extraction for pattern recognition applications, specifically focused on delta and delta-delta parameters. Using MCYT330 online signature database, our experiments show that 11-point approximation outperforms 1-point approximation, resulting in a 1.4% improvement in identification rate, 36.8% reduction in random forgeries and 2.4% reduction in skilled forgeries.-
dc.languageengen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics )[ISSN 0302-9743],v. 14134 LNCS, p. 461-472, (Enero 2023)en_US
dc.subject3307 Tecnología electrónica-
dc.subject.otherDerivatives-
dc.subject.otherDynamic Time Warping-
dc.subject.otherE-Security-
dc.subject.otherOnline Handwriting-
dc.titleOn the Use of First and Second Derivative Approximations for Biometric Online Signature Recognitionen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference17th International Work-Conference on Artificial Neural Networks, IWANN 2023en_US
dc.identifier.doi10.1007/978-3-031-43085-5_36en_US
dc.identifier.scopus85174503559-
dc.identifier.isi001155313400036-
dc.contributor.orcid0000-0003-0605-1282-
dc.contributor.orcid0000-0003-3878-3867-
dc.contributor.authorscopusid57238059400-
dc.contributor.authorscopusid58552611900-
dc.identifier.eissn1611-3349-
dc.description.lastpage472en_US
dc.description.firstpage461en_US
dc.relation.volume14134 LNCSen_US
dc.investigacionCiencias-
dc.type2Actas de congresosen_US
dc.contributor.daisngid912728-
dc.contributor.daisngid1137937-
dc.description.numberofpages12en_US
dc.utils.revisionSí-
dc.contributor.wosstandardWOS:Faundez-Zanuy, M-
dc.contributor.wosstandardWOS:Diaz, M-
dc.date.coverdateEnero 2023en_US
dc.identifier.conferenceidevents150445-
dc.identifier.ulpgcSí-
dc.contributor.buulpgcBU-BASen_US
dc.description.sjr0,606-
dc.description.sjrqQ2-
dc.description.miaricds10,0-
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Física-
crisitem.author.orcid0000-0003-3878-3867-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameDíaz Cabrera, Moisés-
Appears in Collections:Actas de congresos
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