Hierarchical Behavior-Knowledge Space for Highly Reliable Handwritten Numeral Recognition(Pattern Recognition)
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概要
- 論文の詳細を見る
We propose, in this article, the Hierarchical Behavior-Knowledge Space as an extension of Behavior-Knowledge Space. Hierarchical BKS utilizes ranked level individual classifiers, and automatically expands its behavioral knowledge in order to satisfy given reliability requirement. From the statistical view point, its decisions are as optimal as those of original BKS, and the reliability threshold is a lower bound of estimated reliability. Several comparisons with original BKS and unanimous voting are shown with some experiments.
- 一般社団法人電子情報通信学会の論文
- 2007-08-01
著者
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Kim Jin
Kaist Kor
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Suh Jangwon
Division Of Computer Science Department Of Eecs Kaist:(present Office)icube Corp.
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Kim Jin
Division Of Applied Life Science (bk21 Program) Institute Of Agricultural & Life Sciences Depart
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Kim Jin
Division of Advanced Materials Engineering, Chonbuk National University, Jeonju 561-756, Korea
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