首页> 外文会议>IEEE Conference on Industrial Electronics and Applications >Feature decreasing methods using fuzzy rough set based on mutual information
【24h】

Feature decreasing methods using fuzzy rough set based on mutual information

机译:基于互信息的模糊粗糙集特征减少方法

获取原文

摘要

Feature reduction methods are of interest in applications such as content based image and video retrieval. In large multimedia databases, it may not be practical to search through the entire database in order to retrieve the nearest neighbours of a query. Good data structures for similarity search and indexing are needed, and the existing data structures do not scale well for the high dimensional multimedia descriptors. Thus feature reduction is an important step. We investigate the use of rough set for feature reduction. In this paper, we compare three different decreasing methods. They are rough set, fuzzy rough set and fuzzy rough set based on mutual information. From the experimental results, it is shown that the fuzzy rough set based on mutual information can perform better than the other two rough set decreasing methods with increased image retrieval precision.
机译:特征缩减方法在诸如基于内容的图像和视频检索之类的应用中是令人感兴趣的。在大型多媒体数据库中,搜索整个数据库以检索查询的最近邻居可能不切实际。需要用于相似性搜索和索引的良好的数据结构,并且现有的数据结构对于高维多媒体描述符来说不能很好地扩展。因此,特征缩减是重要的一步。我们研究了使用粗糙集进行特征约简。在本文中,我们比较了三种不同的递减方法。它们是基于互信息的粗糙集,模糊粗糙集和模糊粗糙集。从实验结果可以看出,基于互信息的模糊粗糙集可以比其他两种粗糙集减少方法具有更好的图像检索精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号