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eBook Biometric System and Data Analysis: Design, Evaluation, and Data Mining download

by Neil Yager,Ted Dunstone

eBook Biometric System and Data Analysis: Design, Evaluation, and Data Mining download ISBN: 0387776257
Author: Neil Yager,Ted Dunstone
Publisher: Springer; 2009 edition (December 2, 2008)
Language: English
Pages: 268
ePub: 1778 kb
Fb2: 1232 kb
Rating: 4.1
Other formats: doc mobi rtf azw
Category: Technologies
Subcategory: Computer Science

Books on biometrics tend to focus on biometric systems and their components, and differentiate between the various biometric modalities.

Books on biometrics tend to focus on biometric systems and their components, and differentiate between the various biometric modalities. Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. This professional book naturally leads to topics including data mining and prediction, which have been widely applied to other fields but not rigorously to biometrics, to be examined in detail.

Biometric System and Data. has been added to your Cart. This professional book naturally leads to topics including data mining and prediction, widely applied to other fields but not rigorously to biometrics. The evaluation techniques are presented rigorously, however are always accompanied by intuitive explanations that convey the essence of the statistical concepts in a general manner.

It naturally leads to topics including data mining and prediction to be examined in detail. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.

By (author) Ted Dunstone, By (author) Neil Yager.

The evaluation techniques are presented rigorously and are accompanied by intuitive explanations.

Biometric System and Data Analysis Ted Dunstone; Neil Yager Springer 9781441945952 : This book brings together aspects of statistics and machine learning to provide a comprehensive guide to e. The evaluation techniques are presented rigorously and are accompanied by intuitive explanations. Описание: A guide to evaluating, interpreting and understanding biometric data.

Ted Dunstone Neil Yager. Goat, sheep, and lamb are labels for problem users of a biometric system. Biometric System and Data Analysis.

It is commonly accepted that users of a biometric system may have differing degrees of accuracy within the system. These user types are defined in terms of their verification performance when matched against themselves (goats) or when matched against others (lambs and wolves). Four new members of the biometric menagerie are proposed based on a user's relationship between their genuine and imposter match scores.

Biometric system and data analysis: Design, evaluation, and data mining. 2007 IEEE Workshop on Automatic Identification Advanced Technologies, 1-6, 2007. Springer Science & Business Media, 2008. Pattern Analysis and Applications 7 (1), 77-93, 2004. the scikit-image contributors, S Van der Walt, JL Schönberger, J Nunez-Iglesias, F Boulogne,. Scikit-image: image processing in Python, PeerJ 2, e453, 2014. Ted Dunstone, Neil Yager. Biometric systems are being used in more places and on a larger scale than ever before. As these systems mature, it is vital to ensure the practitioners responsible for development and deployment. More). Group Evaluation: Data Mining for Biometrics.

for Biometrics - Special Topics in Biometric Data Analysis - Proof of Identity - Covert Surveillance Systems - Vulnerabilities. Abstract: Biometric System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data. It naturally leads to topics including data mining and prediction to be examined in detail.

This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.