000			03260nam a22005295i 4500
001			978-0-387-77627-9
003			DE-He213
005			20251006084415.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387776279
020			_a99780387776279
024	7		_a10.1007/978-0-387-77627-9 _2doi
082	0	4	_a570.15195 _223
100	1		_aDunstone, Ted. _eeditor.
245	1	0	_aBiometric System and Data Analysis _h[electronic resource] : _bDesign, Evaluation, and Data Mining / _cedited by Ted Dunstone, Neil Yager.
264		1	_aBoston, MA : _bSpringer US, _c2009.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aAn Overview of Biometrics -- An Introduction to Biometric Data Analysis -- Biometric Matching Basics -- Biometric Data -- Multimodal Systems -- Performance Testing and Reporting -- Definitions -- The Biometric Performance Hierarchy -- System Evaluation: The Statistical Basis of Biometric Systems -- Individual Evaluation: The Biometric Menagerie -- Group Evaluation: Data Mining for Biometrics -- Special Topics in Biometric Data Analysis -- Proof of Identity -- Covert Surveillance Systems -- Vulnerabilities.
520			_aBiometric 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. This professional book naturally leads to topics including data mining and prediction, widely applied to other fields but not rigorously to biometrics. This volume 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 are always accompanied by intuitive explanations that convey the essence of the statistical concepts in a general manner. Designed for a professional audience composed of practitioners and researchers in industry, Biometric System and Data Analysis: Design, Evaluation, and Data Mining is also suitable as a reference for advanced-level students in computer science and engineering.
650		0	_aCOMPUTER SCIENCE.
650		0	_aDATA ENCRYPTION (COMPUTER SCIENCE).
650		0	_aDATABASE MANAGEMENT.
650		0	_aDATA MINING.
650		0	_aARTIFICIAL INTELLIGENCE.
650		0	_aCOMPUTER VISION.
650		0	_aBIOMETRICS.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aBIOMETRICS.
650	2	4	_aCOMPUTER IMAGING, VISION, PATTERN RECOGNITION AND GRAPHICS.
650	2	4	_aDATA MINING AND KNOWLEDGE DISCOVERY.
650	2	4	_aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
650	2	4	_aDATA ENCRYPTION.
650	2	4	_aDATABASE MANAGEMENT.
700	1		_aYager, Neil. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387776255
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-77627-9 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c58991 _d58991