Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
554779 | Decision Support Systems | 2011 | 11 Pages |
Abstract
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.
Keywords
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Physical Sciences and Engineering
Computer Science
Information Systems
Authors
Sérgio Francisco da Silva, Marcela Xavier Ribeiro, João do E.S. Batista Neto, Caetano Traina-Jr., Agma J.M. Traina,