A neural network approach to similarity learning

被引：0

作者：

Melacci, Stefano ^{[1
]}

Sarti, Lorenzo ^{[1
]}

Maggini, Marco ^{[1
]}

Bianchini, Monica ^{[1
]}

机构：

[1] Univ Siena, DII, I-53100 Siena, Italy

来源：

ARTIFICIAL NEURAL NETWORKS IN PATTERN RECOGNITION, PROCEEDINGS | 2008年 / 5064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：

This paper presents a novel neural network model, called similarity neural network (SNN), designed to learn similarity measures for pairs of patterns. The model guarantees to compute a non negative and symmetric measure, and shows good generalization capabilities even if a very small set of supervised examples is used for training. Preliminary experiments, carried out on some UCI datasets, are presented, showing promising results.

引用

页码：133 / 136

页数：4

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