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Search Publications by: James Matey (Fed)

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Displaying 26 - 34 of 34

Modest proposals for improving biometric recognition papers

August 31, 2015
Author(s)
James R. Matey, George W. Quinn, Patrick J. Grother, Elham Tabassi, Craig I. Watson, James L. Wayman
We present practical recommendations for improving the clarity, transparency, and usefulness of many biometric papers. Several of the recommendations can be enabled by preparing a publicly available library of state of the art Receiver Operating

IREX IV: Part 1, Evaluation of Iris Identification Algorithms

July 11, 2013
Author(s)
George W. Quinn, Patrick J. Grother, Mei L. Ngan, James R. Matey
IREX IV aims to provide a fair and balanced scientific evaluation of the performance of automated iris recognition algorithms. IREX IV evaluated the performance of 66 identification (i.e. one-to-many matching) algorithms submitted by 12 companies and

IREX VI - Temporal Stability of Iris Recognition Accuracy

July 11, 2013
Author(s)
Patrick J. Grother, James R. Matey, Elham Tabassi, George W. Quinn, Michael Chumakov
Background: Stability is a required definitional property for a biometric to be useful. Quantitative statements of stability are operationally important as they dictate re-enrollment schedules e.g. of a face on a passport. Ophthalmologists consider the

IREX III - Performance of Iris Identification Algorithms

April 3, 2012
Author(s)
Patrick J. Grother, George W. Quinn, James R. Matey, Mei L. Ngan, Wayne J. Salamon, Gregory P. Fiumara, Craig I. Watson
Iris recognition has long been held as an accurate and fast biometric. In the first public evaluation of one-to-many iris identification technologies, this third activity in the Iris Exchange (IREX) program has measured the core algorithmic efficacy and