Multimodal Similarity-Preserving Hashing

Multimodal Similarity-Preserving Hashing

We introduce an efficient computational framework for hashing data belonging to multiple modalities into a single representation space where they become mutually comparable. The proposed approach is based on a novel coupled siamese neural network architecture and allows unified treatment of intra- a...

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Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 36(2014), 4 vom: 01. Apr., Seite 824-30
Auteur principal: Masci, Jonathan (Auteur)
Autres auteurs: Bronstein, Michael M, Bronstein, Alexander M, Schmidhuber, Jürgen
Format: Article en ligne
Langue:English
Publié: 2014
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article Research Support, Non-U.S. Gov't
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