Texture classification using kernel logistic regression

被引：0

作者：

Tambo, Asongu L. ^{[1
]}

Mistry, Rajan B. ^{[1
]}

Campbell, Jonathan M. ^{[1
]}

Chan, Sherwin R. ^{[1
]}

Hang, Xiyi ^{[1
]}

机构：

[1] Calif State Univ Northridge, Dept Elect & Comp Engn, Northridge, CA 93063 USA

来源：

INT CONF ON CYBERNETICS AND INFORMATION TECHNOLOGIES, SYSTEMS AND APPLICATIONS/INT CONF ON COMPUTING, COMMUNICATIONS AND CONTROL TECHNOLOGIES, VOL 1 | 2007年

关键词：

texture; classification; machine learning; kernel logistic regression; support vector machine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates the application of Kernel Logistic Regression (KLR) in texture classification. Stationary wavelet transform is used for feature extraction. The numerical experiment shows that when it comes to texture classification, KLR is comparable to popular support vector machine (SVM).

引用

页码：259 / 262

页数：4

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