计算机应用研究Issue(2)：606-608,618,4.DOI:10.3969/j.issn.1001-3695.2015.02.064
基于 Hessian半监督特征选择的网络图像标注
Web image annotation based on Hessian semi-supervised feature selection
摘要
Abstract
This paper researched and applied semi-supervised feature selection method,which exploited the labeled data and unlabeled data simultaneously,to improve the performance of Web image annotation.It proposed a novel semi-supervised fea-ture selection method based on the second-order Hessian energy,which could preserve local topology better and had good ex-trapolation capability to overcome the drawbacks of methods based on Laplacian.It applied the proposed method to Web image annotation task and performed extensive experiments on two large-scale Web image datasets.The results show that the proposed method is superior to methods based on Lapacian and suitable for large-scale Web image annotation.关键词
网络图像标注/半监督学习/Hessian 能/特征选择Key words
Web image annotation/semi-supervised learning/Hessian energy/feature selection分类
信息技术与安全科学引用本文复制引用
史彩娟,阮秋琦,刘健,闫晓东..基于 Hessian半监督特征选择的网络图像标注[J].计算机应用研究,2015,(2):606-608,618,4.基金项目
国家自然科学基金资助项目（61172128）；国家“973”计划资助项目（2012CB316304）；国家教育部新世纪优秀人才支持计划资助项目（NCET-12-0768）；中央高校基本科研基金资助项目（2013jbm020，2013jbz003）；国家教育部高校科研创新团队发展计划资助项目（IRT201206）；北京高校“青年英才计划”资助项目（YETP0544）；国家教育部博士点基金资助项目（20120009110008，20120009120009）；河北省高等学校科学研究青年基金资助项目 （）
