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Credence estimation and error prediction in biometric identity verification

机译:生物特征身份验证中的凭据估计和错误预测

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摘要

This paper focuses on the estimation of credence in the correctness of classification decisions produced by a biometric identity veriiication system. We adopt the concept of decision credence defined in terms of subjective Bayesian degree of belief. We demonstrate how credence estimates can be used to predict verification errors and to rectify them, thus improving the classification performance. We also show how the framework of credence estimation helps handle erroneous classification decisions thanks to seamless incorporation of quality measures. Further, we demonstrate that credence information can be effectively applied to perform fusion of decisions in a multimodal scenario.
机译:本文着重于对由生物特征身份验证系统产生的分类决策的正确性的可信度估计。我们采用基于主观贝叶斯信念程度定义的决策信任度的概念。我们演示了可信度估计如何可用于预测验证错误并纠正它们,从而提高分类性能。我们还展示了信誉评估框架如何通过无缝整合质量度量来帮助处理错误的分类决策。此外,我们证明了信用信息可以有效地应用于多模式方案中的决策融合。

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