Hash Function Learning Via Codewords

Keywords

Codeword; Hash function learning; Support vector machine

Abstract

In this paper we introduce a novel hash learning framework that has two main distinguishing features, when compared to past approaches. First, it utilizes codewords in the Hamming space as ancillary means to accomplish its hash learning task. These codewords, which are inferred from the data, attempt to capture similarity aspects of the data’s hash codes. Secondly and more importantly, the same framework is capable of addressing supervised, unsupervised and, even, semisupervised hash learning tasks in a natural manner. A series of comparative experiments focused on content-based image retrieval highlights its performance advantages.

Publication Date

1-1-2015

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

9284

Number of Pages

659-674

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-23528-8_41

Socpus ID

84984633404 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84984633404

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