Multi-modal Hash Learning

Multi-modal Hash Learning

AngličtinaMäkká väzbaTlač na objednávku
Zhu Lei
Springer, Berlin
EAN: 9783031372933
Tlač na objednávku
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Podrobné informácie

This book systemically presents key concepts of multi-modal hashing technology, recent advances on large-scale efficient multimedia search and recommendation, and recent achievements in multimedia indexing technology.  With the explosive growth of multimedia contents, multimedia retrieval is currently facing unprecedented challenges in both storage cost and retrieval speed. The multi-modal hashing technique can project high-dimensional data into compact binary hash codes. With it, the most time-consuming semantic similarity computation during the multimedia retrieval process can be significantly accelerated with fast Hamming distance computation, and meanwhile the storage cost can be reduced greatly by the binary embedding.  The authors introduce the categorization of existing multi-modal hashing methods according to various metrics and datasets. The authors also collect recent multi-modal hashing techniques and describe the motivation, objective formulations, and optimization steps for context-aware hashing methods based on the tag-semantics transfer.  


EAN 9783031372933
ISBN 303137293X
Typ produktu Mäkká väzba
Vydavateľ Springer, Berlin
Dátum vydania 23. augusta 2024
Stránky 199
Jazyk English
Rozmery 240 x 168
Krajina Switzerland
Autori Guan, Weili; Li, Jingjing; Zhu Lei
Edícia 2024 ed.
Séria Synthesis Lectures on Information Concepts, Retrieval, and Services