Image classification: an evolutionary approach

被引：31

作者：

Agnelli, D ^{[1
]}

Bollini, A ^{[1
]}

Lombardi, L ^{[1
]}

机构：

[1] Univ Pavia, Dipartimento Informat & Sistemist, I-27100 Pavia, Italy

来源：

PATTERN RECOGNITION LETTERS | 2002年 / 23卷 / 1-3期

关键词：

image classification; genetic programming; supervised learning;

D O I：

10.1016/S0167-8655(01)00128-3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Evolutionary algorithms are proving viable in solving complex optimization problems such as those typical of supervised learning approaches to image understanding. This paper presents an evolutionary approach to image classification and discusses some experimental results, suggesting that genetic programming could provide a convenient alternative to standard supervised learning methods. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：303 / 309

页数：7

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