计算机应用与软件Issue(9)：263-265,295,4.DOI:10.3969/j.issn.1000-386x.2013.09.072
一种基于层次语义图像分类的改进方法
AN IMPROVEMENT METHOD BASED ON HIERARCHICAL SEMANTIC IMAGES CLASSIFICATION
孙延鹏 1徐思敏1
作者信息
- 1. 沈阳航空航天大学电子信息工程学院 辽宁 沈阳 110136
- 折叠
摘要
Abstract
This paper uses two solutions for the problem of low classification rate in hierarchical semantic images , in particular the high-level hierarchical semantic images .Firstly we introduce the theory of fuzzy support vector machine ( FSVM ) and improve it , this eliminates the unclassifiable region of the multi-class classifiers constructed with support vector machine ( SVM ) , therefore the image classification accuracy rate of lower-level semantic images is enhanced;it provides a basis for the high-level semantic classification .Then, we establish the mapping relationship between the bottom image characteristics and the lower-level semantic images for making the association of high-level semantics for low-level semantic image , and finally achieve the hierarchical semantic description structure .Experimental results show that the presented method can improve the classification accuracy rate of hierarchical semantic images , especially of the high-level hierarchical semantic images .关键词
支持矢量机/模糊支持矢量机/层次语义/图像分类Key words
SVM/FSVM/Hierarchical semantics/Image classification分类
信息技术与安全科学引用本文复制引用
孙延鹏,徐思敏..一种基于层次语义图像分类的改进方法[J].计算机应用与软件,2013,(9):263-265,295,4.
