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
收藏
页码：133 / 136
页数：4
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