Relationship Between Errors of Supplementary Information andMisrecognition Rates
Journal
IEICE Technical Report
Presentation number
PRMU2007-152
Pages
pp.95-100
Reviewed
Not reviewed
Date
December 2007
Research fields
Pattern recognition
Key
Furuya2007 (id=1003)
Abstract
Pattern recognition with supplementary information is a new pattern recognition framework that determines
an output class by combining a classifier’s output and supplementary information suggesting the true class.
Under the condition that supplementary information does not contain error, we have proposed a theory that reduces
misrecognition rates. However, in the real world, we cannot observe any measure without error. Thus, in this
paper, we discuss how to reduce misrecognition rates using the erroneous supplementary information, and show the
possibility to reduce misrecognition rates experimentally.
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