期刊
DECISION SUPPORT SYSTEMS
卷 51, 期 4, 页码 810-820出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.dss.2011.01.015
关键词
Feature selection; Genetic algorithms; Ranking quality; Medical image retrieval
类别
资金
- CNPq [306726 2009-2]
- CAPES
- FAPESP
- STIC-AmSud
- Microsoft Research
In this paper, we take advantage of single-valued functions that evaluate rankings to develop a family of feature selection methods based on the genetic algorithm approach, tailored to improve the accuracy of content-based image retrieval systems. Experiments on three image datasets, comprising images of breast and lung nodules, showed that developing functions to evaluate the ranking quality allows improving retrieval performance. This approach produces significantly better results than those of other fitness function approaches, such as the traditional wrapper and than filter feature selection algorithms. (C) 2011 Elsevier B.V. All rights reserved.
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