Score Fusion by Maximizing the Area under the ROC Curve

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dc.contributor.affiliationDepartamento de Sistemas Informáticos y Computación
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería Informática
dc.contributor.affiliationCentro de Investigación Pattern Recognition and Human Language Technology
dc.contributor.authorVillegas Santamaría, Mauricioes_ES
dc.contributor.authorParedes Palacios, Roberto
dc.contributor.funderMinisterio de Ciencia e Innovaciónes_ES
dc.contributor.funderGeneralitat Valencianaes_ES
dc.contributor.funderMinisterio de Educación y Cienciaes_ES
dc.date.accessioned2014-11-11T12:43:12Z
dc.date.available2014-11-11T12:43:12Z
dc.date.issued2009
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02172-5_61es_ES
dc.description.abstractInformation fusion is currently a very active research topic aimed at improving the performance of biometric systems. This paper proposes a novel method for optimizing the parameters of a score fusion model based on maximizing an index related to the Area Under the ROC Curve. This approach has the convenience that the fusion parameters are learned without having to specify the client and impostor priors or the costs for the different errors. Empirical results on several datasets show the effectiveness of the proposed approach.es_ES
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationVillegas Santamaría, M.; Paredes Palacios, R. (2009). Score Fusion by Maximizing the Area under the ROC Curve. En Pattern Recognition and Image Analysis: 4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedings. Springer Verlag (Germany). 473-480. https://doi.org/10.1007/978-3-642-02172-5_61es_ES
dc.description.referencesToh, K.A., Kim, J., Lee, S.: Biometric scores fusion based on total error rate minimization. Pattern Recognition 41(3), 1066–1082 (2008)es_ES
dc.description.referencesJain, A., Nandakumar, K., Ross, A.: Score normalization in multimodal biometric systems. Pattern Recognition 38(12), 2270–2285 (2005)es_ES
dc.description.referencesGutschoven, B., Verlinde, P.: Multi-modal identity verification using support vector machines (svm). In: Proceedings of the Third International Conference on Information Fusion. FUSION 2000, vol. 2, pp. THB3/3–THB3/8 (July 2000)es_ES
dc.description.referencesMa, Y., Cukic, B., Singh, H.: A classification approach to multi-biometric score fusion. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 484–493. Springer, Heidelberg (2005)es_ES
dc.description.referencesMaurer, D.E., Baker, J.P.: Fusing multimodal biometrics with quality estimates via a bayesian belief network. Pattern Recogn. 41(3), 821–832 (2008)es_ES
dc.description.referencesLing, C.X., Huang, J., Zhang, H.: Auc: a statistically consistent and more discriminating measure than accuracy. In: Proc. of IJCAI 2003, pp. 519–524 (2003)es_ES
dc.description.referencesYan, L., Dodier, R.H., Mozer, M., Wolniewicz, R.H.: Optimizing classifier performance via an approximation to the wilcoxon-mann-whitney statistic. In: Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), Washington, DC, USA, pp. 848–855. AAAI Press, Menlo Park (2003)es_ES
dc.description.referencesMarrocco, C., Molinara, M., Tortorella, F.: Exploiting auc for optimal linear combinations of dichotomizers. Pattern Recogn. Lett. 27(8), 900–907 (2006)es_ES
dc.description.referencesMarrocco, C., Duin, R.P.W., Tortorella, F.: Maximizing the area under the roc curve by pairwise feature combination. Pattern Recogn. 41(6), 1961–1974 (2008)es_ES
dc.description.referencesParedes, R., Vidal, E.: Learning prototypes and distances: a prototype reduction technique based on nearest neighbor error minimization. Pattern Recognition 39(2), 180–188 (2006)es_ES
dc.description.referencesVillegas, M., Paredes, R.: Simultaneous learning of a discriminative projection and prototypes for nearest-neighbor classification. In: IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2008, pp. 1–8 (2008)es_ES
dc.description.referencesNandakumar, K., Chen, Y., Dass, S.C., Jain, A.: Likelihood ratio-based biometric score fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2), 342–347 (2008)es_ES
dc.description.referencesPoh, N., Bengio, S.: A score-level fusion benchmark database for biometric authentication. In: Kanade, T., Jain, A., Ratha, N.K. (eds.) AVBPA 2005. LNCS, vol. 3546, pp. 1059–1070. Springer, Heidelberg (2005)es_ES
dc.description.referencesNational Institute of Standards and Technology: NIST Biometric Scores Set - Release 1 (BSSR1) (2004), http://www.itl.nist.gov/iad/894.03/biometricscores/es_ES
dc.description.referencesBengio, S., Mariéthoz, J., Keller, M.: The expected performance curve. In: Proceedings of the Second Workshop on ROC Analysis in ML, pp. 9–16 (2005)es_ES
dc.description.sponsorshipWork supported by the Spanish projects DPI2006-15542-C04 and TIN2008-04571 and the Generalitat Valenciana - Consellería d’Educació under an FPI scholarship.es_ES
dc.description.upvformatpfin480es_ES
dc.description.upvformatpinicio473es_ES
dc.identifier.doi10.1007/978-3-642-02172-5_61
dc.identifier.isbn978-3-642-02171-8
dc.identifier.issn0302-9743
dc.identifier.urihttps://riunet.upv.es/handle/10251/44043
dc.languageIngléses_ES
dc.publisherSpringer Verlag (Germany)es_ES
dc.relation.ispartofPattern Recognition and Image Analysis: 4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedingses_ES
dc.relation.ispartofseriesLecture Notes in Computer Science;5524
dc.relation.projectIDinfo:eu-repo/grantAgreement/MEC//DPI2006-15542-C04-02/ES/APLICACION INDUSTRIAL DE TECNICAS AVANZADAS DE RECONOCIMIENTO DE FORMAS Y VISION ARTIFICIAL/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN//TIN2008-04571/ES/RISE: RELEVANCE IMAGE SEARCH ENGINE/es_ES
dc.relation.publisherversionhttp://link.springer.com/chapter/10.1007/978-3-642-02172-5_61es_ES
dc.relation.references10.1016/j.patcog.2007.07.020es_ES
dc.relation.references10.1016/j.patcog.2005.01.012es_ES
dc.relation.references10.1109/IFIC.2000.859876es_ES
dc.relation.references10.1007/11527923_50es_ES
dc.relation.references10.1016/j.patcog.2007.08.008es_ES
dc.relation.references10.1016/j.patrec.2005.10.014es_ES
dc.relation.references10.1016/j.patcog.2007.11.017es_ES
dc.relation.references10.1016/j.patcog.2005.06.001es_ES
dc.relation.references10.1109/CVPR.2008.4587590es_ES
dc.relation.references10.1109/TPAMI.2007.70796es_ES
dc.relation.references10.1007/11527923_110es_ES
dc.relation.senia36642
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subject.classificationLENGUAJES Y SISTEMAS INFORMATICOSes_ES
dc.titleScore Fusion by Maximizing the Area under the ROC Curvees_ES
dc.typeCapítulo de libroes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
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