Score Fusion by Maximizing the Area under the ROC Curve
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https://riunet.upv.es/handle/10251/44043
Cita bibliográfica
Villegas 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_61
Titulación
Resumen
Information 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.
Descripción
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02172-5_61
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Fuente
Pattern Recognition and Image Analysis: 4th Iberian Conference, IbPRIA 2009 Póvoa de Varzim, Portugal, June 10-12, 2009 Proceedings isbn: 978-3-642-02171-8 issn: 0302-9743
Editorial
Springer Verlag (Germany)