Abstract of A Review on Multi-Attribute Assisted Reranking usi
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064

Downloads: 116

Review Papers | Computer Science & Engineering | India | Volume 5 Issue 11, November 2016

A Review on Multi-Attribute Assisted Reranking using SVM Classification for Web Image Search

Sarika Yekule, Anil D. Gujar

This review paper formulates an image reranking problem to improve Text Based Information Retrieval (TBIR) by using Multi-attribute learning methods. Existing methods train separate classifier for each word and heuristically combine outputs for retrieving multiword query. The proposed work partition relevant images into clusters, known as container, by using visual and textual attributes. Based on multi-attributes learning we cluster multiple relevant images in positive container whereas few relevant images are clustered with irrelevant images in negative container. Further we enhance multi-attribute learning algorithm to effectively rerank relevant images.

Keywords: image retrieval, attribute-assisted, search, SVM, Multiple-instance learning, CBIR

Edition: Volume 5 Issue 11, November 2016

Pages: 1605 - 1607

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How to Cite this Article?

Sarika Yekule, Anil D. Gujar, "A Review on Multi-Attribute Assisted Reranking using SVM Classification for Web Image Search", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20163161, Volume 5 Issue 11, November 2016, 1605 - 1607

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