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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2012.2222902
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|a eng
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|a Wei, Xiao-Yong
|e verfasserin
|4 aut
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|a Coaching the exploration and exploitation in active learning for interactive video retrieval
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|c 2013
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|a Text
|b txt
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Completed 18.07.2013
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|a Date Revised 30.01.2013
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Conventional active learning approaches for interactive video/image retrieval usually assume the query distribution is unknown, as it is difficult to estimate with only a limited number of labeled instances available. Thus, it is easy to put the system in a dilemma whether to explore the feature space in uncertain areas for a better understanding of the query distribution or to harvest in certain areas for more relevant instances. In this paper, we propose a novel approach called coached active learning that makes the query distribution predictable through training and, therefore, avoids the risk of searching on a completely unknown space. The estimated distribution, which provides a more global view of the feature space, can be used to schedule not only the timing but also the step sizes of the exploration and the exploitation in a principled way. The results of the experiments on a large-scale data set from TRECVID 2005-2009 validate the efficiency and effectiveness of our approach, which demonstrates an encouraging performance when facing domain-shift, outperforms eight conventional active learning methods, and shows superiority to six state-of-the-art interactive video retrieval systems
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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700 |
1 |
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|a Yang, Zhen-Qun
|e verfasserin
|4 aut
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773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 22(2013), 3 vom: 01. März, Seite 955-68
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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|g volume:22
|g year:2013
|g number:3
|g day:01
|g month:03
|g pages:955-68
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|u http://dx.doi.org/10.1109/TIP.2012.2222902
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