Autoencoder-based self-supervised hashing for cross-modal retrieval

Cross-modal retrieval has gained lots of attention in the era of the multimedia data explosion. Taking advantage of low storage cost and fast retrieval speed, hash learning-based methods become more and more popular in this field. The crucial bottlenecks of cross-modal retrieval are twofold: the het...

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Veröffentlicht in:	Multimedia tools and applications Jg. 80; H. 11; S. 17257 - 17274
Hauptverfasser:	Li, Yifan, Wang, Xuan, Cui, Lei, Zhang, Jiajia, Huang, Chengkai, Luo, Xuan, Qi, Shuhan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.05.2021 Springer Nature B.V
Schlagworte:	Computer Communication Networks Computer Science Data Structures and Information Theory Multimedia Multimedia Information Systems Retrieval Semantics Special Purpose and Application-Based Systems Self-supervised Cross-modal retrieval Autoencoder Hash learning
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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