An Optimized Method for Face Recognition Using PCA and PSO Techniques

被引：0

作者：

Chaimaa, Khoudda ^{[1
]}

El Miloud, Smaili ^{[1
]}

Salma, Azzouzi ^{[1
]}

Charaf, My El Hassan ^{[1
]}

机构：

[1] IbnTofail Univ, Fac Sci, Kenitra, Morocco

来源：

ADVANCED INTELLIGENT SYSTEMS FOR SUSTAINABLE DEVELOPMENT (AI2SD'2020), VOL 2 | 2022年 / 1418卷

关键词：

Face recognition; PSO; PCA; Optimization; IMAGE;

D O I：

10.1007/978-3-030-90639-9_63

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Optimizing extracted facial features remains a critical issue inmachine learning that aims to provide acceptable recognition accuracy by reducing the number of features, removing noisy and redundant data. This paper presents a new approach based on the combination of Principal Component Analysis (PCA) and Particle swarm optimization (PSO) to grant an optimal selection of distinctive facial information using the Olivetti Research Laboratory (ORL) database.

引用

页码：762 / 773

页数：12

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