On-line signature verification using Gaussian Mixture Models and small-sample learning strategies/Verificación de firmas en línea usando modelos de mezcla Gaussianas y estrategias de aprendizaje para conjuntos pequeños de muestras

This paper addresses the problem of training on-line signature verification systems when the number of training samples is small, facing the real-world scenario when the number of available signatures per user is limited. The paper evaluates nine different classification strategies based on Gaussian...

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Veröffentlicht in:	Revista Facultad de Ingeniería 2016-06 (79), p.84-84
Hauptverfasser:	Zapata-Zapata, Gabriel Jaime, Arias-Londoño, Julián David, Vargas-Bonilla, Jesús Francisco, Orozco-Arroyave, Juan Rafael
Format:	Artikel
Sprache:	eng ; spa
Schlagworte:	Accuracy Algorithms Bayesian analysis Biometrics Digital signatures Experiments Learning Methods Pattern recognition systems Signatures Strategy Support vector machines Training
Online-Zugang:	Volltext
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