Publication Type

Conference Paper

Publication Date

5-2004

Abstract

Without textual descriptions or label information of images, searching semantic concepts in image databases is still a very challenging task. While automatic annotation techniques are yet a long way off, we can seek other alternative techniques to solve this difficult issue. In this paper, we propose to learn Web images for searching the semantic concepts in large image databases. To formulate effective algorithms, we suggest to engage the support vector machines for attacking the problem. We evaluate our algorithm in a large image database and demonstrate the preliminary yet promising results.

Keywords

Web Image Learning, Semantic Searching, Image Retrieval, RelevanceFeedback, Support Vector Machine

Discipline

Computer Sciences

Publication

In Proceedings of 13th International World Wide Web Conference (WWW2004)

Identifier

10.1145/1013367.1013498

City or Country

New York, USA

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