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Multiple layar kernel-based approach in relevance feedback content-based image retrieval system

Chung, K.P. and Fung, C.C. (2005) Multiple layar kernel-based approach in relevance feedback content-based image retrieval system. In: 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, 18-21 Aug. 2005, Guangzhou, China pp. 405-409.

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    Link to Published Version: http://dx.doi.org/10.1109/ICMLC.2005.1526981
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    Abstract

    Relevance feedback has drawn intense interest from many researchers in the field of content-based image retrieval (CBIR). In recent years, kernel-based approach has been a popular choice for the implementation of the relevance feedback based CBIR system. This is largely due to its ability to classify patterns with limited sample data. Since most of the kernel approaches reported have been treating the input as a long flat vector, such arrangement may increase the chances of polluting the feature element that uniquely identifies the selected image group. This paper proposes a two layer kernel configuration with an objective to improve the retrieval accuracy. While the performance of the two configurations is similar in certain conditions, the proposed configuration has shown to superior when dominant feature element exists that is capable to uniquely identify the selected image group.

    Publication Type: Conference Paper
    Murdoch Affiliation: School of Information Technology
    Publisher: IEEE
    Copyright: (c) 2005 IEEE.
    Notes: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    URI: http://researchrepository.murdoch.edu.au/id/eprint/603
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