Co-Training on Handwritten Digit Recognition

被引：0

作者：

Du, Jun ^{[1
]}

Ling, Charles X. ^{[1
]}

机构：

[1] Univ Western Ontario, Dept Comp Sci, London, ON N6A 5B7, Canada

来源：

ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2009年 / 5549卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we apply a semi-supervised learning paradigm - co-training to handwritten digit recognition, so as to construct high-performance recognition model with very few labeled images. Experimental results show that; based on arbitrary two types of given features, co-training can always achieve high accuracy. Thus, it provides a generic and robust approach to construct high performance model with very few labeled handwritten digit images.

引用

页码：203 / +

页数：2

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