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|a 10.1109/TIP.2014.2378057
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|a eng
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1 |
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|a Hsiao, Ko-Jen
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Pareto-depth for multiple-query image retrieval
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|c 2015
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|a Text
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|a Date Completed 30.03.2015
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|a Date Revised 14.01.2015
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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|a Calder, Jeff
|e verfasserin
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1 |
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|a Hero, Alfred O
|c 3rd
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|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 24(2015), 2 vom: 08. Feb., Seite 583-94
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