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Sensitivity Analysis for Biometric Systems
Sensitivity Analysis for Biometric Systems
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34,29 €
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The purpose of this paper is to introduce an effective and structured methodology for carrying out a biometric system sensitivity analysis. The goal of sensitivity analysis is to provide the researcher/developer with the insight and understanding of the key factors-algorithmic, subject-based, camera-based, procedural, image quality, environmental, among others-that affect the matching performance of the biometric system under study. This proposed methodology consists of two steps: 1) the design…
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The purpose of this paper is to introduce an effective and structured methodology for carrying out a biometric system sensitivity analysis. The goal of sensitivity analysis is to provide the researcher/developer with the insight and understanding of the key factors-algorithmic, subject-based, camera-based, procedural, image quality, environmental, among others-that affect the matching performance of the biometric system under study. This proposed methodology consists of two steps: 1) the design and execution of orthogonal fractional factorial experiment designs which allows the scientist to efficiently investigate the effect of a large number of factors-and interactions-simultaneously, and 2) the use of a select set of statistical data analysis graphical procedures which are fine-tuned to unambiguously highlight important factors, important interactions, and locally-optimal settings.

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The purpose of this paper is to introduce an effective and structured methodology for carrying out a biometric system sensitivity analysis. The goal of sensitivity analysis is to provide the researcher/developer with the insight and understanding of the key factors-algorithmic, subject-based, camera-based, procedural, image quality, environmental, among others-that affect the matching performance of the biometric system under study. This proposed methodology consists of two steps: 1) the design and execution of orthogonal fractional factorial experiment designs which allows the scientist to efficiently investigate the effect of a large number of factors-and interactions-simultaneously, and 2) the use of a select set of statistical data analysis graphical procedures which are fine-tuned to unambiguously highlight important factors, important interactions, and locally-optimal settings.

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