NIST · ИТ · beba8336280f07f5cdf1
An Empirical Study of Sample Size in ROC-Curve Analysis of Fingerprint Data
The fingerprint datasets in many cases may exceed millions of samples. Thus, the needed size of a biometric evaluation test sample is an important issue in terms of both accuracy and efficiency. In this article, an empirical study, namely, using Chebyshev
NIST · ИТОфициальный источник · 2006-12-04
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"title_en": "An Empirical Study of Sample Size in ROC-Curve Analysis of Fingerprint Data",
"designation": "",
"series": "",
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"date": "2006-12-04",
"date_original": "December 4, 2006",
"url": "https://www.nist.gov/publications/empirical-study-sample-size-roc-curve-analysis-fingerprint-data",
"source": "NIST Publications",
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"authors_en": "Jin Chu Wu , Charles Wilson",
"abstract_excerpt_en": "The fingerprint datasets in many cases may exceed millions of samples. Thus, the needed size of a biometric evaluation test sample is an important issue in terms of both accuracy and efficiency. In this article, an empirical study, namely, using Chebyshev",
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{
"title_en": "An Empirical Study of Sample Size in ROC-Curve Analysis of Fingerprint Data",
"designation": "",
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"date": "2006-12-04",
"date_original": "December 4, 2006",
"url": "https://www.nist.gov/publications/empirical-study-sample-size-roc-curve-analysis-fingerprint-data",
"source": "NIST Publications",
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"authors_en": "Jin Chu Wu , Charles Wilson",
"abstract_excerpt_en": "The fingerprint datasets in many cases may exceed millions of samples. Thus, the needed size of a biometric evaluation test sample is an important issue in terms of both accuracy and efficiency. In this article, an empirical study, namely, using Chebyshev"
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