A modular classification scheme with elastic net models for handwritten digit recognition

被引：0

作者：

Zhang, BL ^{[1
]}

Fu, MY ^{[1
]}

Yan, H ^{[1
]}

机构：

[1] Univ Newcastle, Dept Elect & Comp Engn, Newcastle, NSW 2308, Australia

来源：

FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2 | 1998年

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：

This paper describes a modular classification system for handwritten digit recognition based on the elastic net model. We use ten separate elastic nets to capture different features in the ten classes of handwritten digits and represent an input sample from the activations in each net by population decoding. Compared with traditional neural net works based discriminant classifiers, our scheme features fast training and high recognition accuracy.

引用

页码：1859 / 1861

页数：3

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