A Domain Independent Genetic Programming Approach to Automatic Feature Extraction for Image Classification

被引：0
|
作者：
Atkins, Daniel [1 ]
Neshatian, Kourosh [1 ]
Zhang, Mengjie [1 ]
机构：
[1] Victoria Univ Wellington, Sch Engn & Comp Sci, Wellington 6140, New Zealand
来源：
2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper we explore the application of Genetic Programming (GP) to the problem of domain-independent image feature extraction and classification. We propose a new GP-based image classification system that extracts image features autonomously, and compare its performance against a baseline GP-based classifier system that uses human-extracted features. We found that the proposed system has a similar performance to the baseline system, and that GP is capable of evolving a single program that can both extract useful features and use those features to classify an image.
引用
收藏
页码：238 / 245
页数：8
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