信息与控制2011，Vol.40Issue(3)：289-295,7.DOI:10.3724/SP.J.1219.2011.00289
基于半监督线性近邻传递的相关反馈方法
Relevance Feedback Algorithm Based on Semi-supervised Linear Neighborhood Propagation
摘要
Abstract
A feedback semi-supervised linear neighborhood propagation method (FSLNP) is proposed. FSLNP method can not only preserve the positive and negative constraints but also preserve the local and global relevance structure infor mation of the whole graph. With both labeled and unLabeled images in relevance feedbacks, a better structure for relevance representation among images is found to reveal the semantic structure. Experimental results show that FSLNP can effectively improve retrieval accuracy, and after long term learning, an optimal relevance graph space can be obtained.关键词
相关反馈/半监督学习/图像检索/线性近邻传递Key words
relevance feedback/ semi-supervised learning/ image retrieval/ linear neighborhood propagation分类
信息技术与安全科学引用本文复制引用
黄传波,金忠..基于半监督线性近邻传递的相关反馈方法[J].信息与控制,2011,40(3):289-295,7.基金项目
国家自然科学基金资助项目(60873151,60973098,90820306). （60873151,60973098,90820306）
