Self-adaptive Biometric Classifier Working on the Reduced Dataset

被引：0

作者：

Porwik, Piotr ^{[1
]}

Doroz, Rafal ^{[1
]}

机构：

[1] Univ Silesia, Inst Comp Sci, PL-41200 Katowice, Poland

来源：

HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS, HAIS 2014 | 2014年 / 8480卷

关键词：

Hotelling's statistics; classification; recognition; biometrics;

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：

The paper presents a method of object recognition by means of a reduced data set. These data are specially prepared. The proposed method was also compared with two other well-known data reduction techniques, Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Objects can mostly be described through many features but these features can have different discriminant powers. The Hotelling's statistical method, allows determining the best discriminatory features and similarity measures which can be simultaneously selected.

引用

页码：377 / 388

页数：12

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