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基于多类SVM相关反馈技术的研究 被引量：2

Research on relevance feedback algorithm based on multi-class SVM
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摘要 相关反馈技术是提高图像检索性能的一个重要手段,本文提出了一种新的基于多类SVM的图像相关反馈检索方法,检索结果表明多类SVM方法在检索性能上具有较其他检索方法更高的检索准确性,并且其检索的密集度较传统SVM检索方法更优. Relevance feedback is an important research field in image retrieval. A novel image relevance Feedback algorithm is proposed in this paper. The experiment indicates that this algorithm gets higher accuracy in retrieval performance than others, also has better dense performance than the retrieval algorithm based on normal SVM methods.
作者 郭金旭 王昱
机构地区 武汉理工大学信息工程学院
出处 《华中师范大学学报（自然科学版）》 CAS CSCD 2008年第3期355-358,共4页 Journal of Central China Normal University：Natural Sciences
基金 公安部创新基金项目(2007YYCXHBST068)
关键词 多类SVM 图像检索 相关反馈 multi-class SVM image retrieval relevance feedback
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献9

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二级参考文献8

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共引文献38

同被引文献26

  • 1冯伟兴,梁洪,王臣业.VisualC+ +数字图像模式识别典型案例详解[M].北京:机械工业出版社,2012: 159-162.
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引证文献2

二级引证文献2

华中师范大学学报（自然科学版）
2008年 第3期

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