Modeling intra- and inter-pair correlation via heterogeneous high-order preserving for cross-modal retrieval
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- 作者：Leiquan Wanga ; b ; richiewlq@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Weichen Suna ; weichen.sun@hotmail.com" class="auth_mail" title="E-mail the corresponding author ; Zhicheng Zhaoa ; zhaozc@bupt.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Fei Sua ; sufei@bupt.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Cross-modal retrieval ; Heterogeneous high-order preserving ; Correlation learning ; Kernel
- 刊名：Signal Processing
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：131
- 期：Complete
- 页码：249-260
- 全文大小：1409 K
文摘
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High-order relationship is used to discover the structure of cross-modal data.
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A kernel version is developed to deal with the nonlinear cross-modal correlation.
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Both supervised and unsupervised scenarios are considered for cross-modal learning.
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High-order, semantic and nonlinear is included for cross-modal correlation.