东华大学学报（英文版）2007，Vol.24Issue(5)：662-666,5.
Image Semantic Automatic Annotation by Relevance Feedback
Image Semantic Automatic Annotation by Relevance Feedback
ZHANG Tong-zhen 1SHEN Rui-min1
作者信息
- 1. Department of Computer Science and Engineering, Shanghai Jiaotong University,Shanghai 200240, China
- 折叠
摘要
Abstract
A large semantic gap exists between content based index retrieval (CBIR) and high-level semantic, additional semantic information should be attached to the images, it refers in three respects including semantic representation model, semantic information building and semantic retrieval techniques. In this paper, we introduce an associated semantic network and an automatic semantic annotation system. In the system, a semantic network model is employed as the semantic representation model, it uses semantic keywords, linguistic ontology and low-level features in semantic similarity calculating. Through several times of users' relevance feedback, semantic network is enriched automatically. To speed up the growth of semantic network and get a balance annotation, semantic seeds and semantic loners are employed especially.关键词
semantic annotation / relevance feedback / semantic seeds and lonersKey words
semantic annotation / relevance feedback / semantic seeds and loners分类
信息技术与安全科学引用本文复制引用
ZHANG Tong-zhen,SHEN Rui-min..Image Semantic Automatic Annotation by Relevance Feedback[J].东华大学学报（英文版）,2007,24(5):662-666,5.
