Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval
Joint Authors
Zhao, Chongyang
Miao, Jun
Su, Xing
Duan, Lijuan
Qiao, Yuanhua
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-24
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Hashing has been widely deployed to perform the Approximate Nearest Neighbor (ANN) search for the large-scale image retrieval to solve the problem of storage and retrieval efficiency.
Recently, deep hashing methods have been proposed to perform the simultaneous feature learning and the hash code learning with deep neural networks.
Even though deep hashing has shown the better performance than traditional hashing methods with handcrafted features, the learned compact hash code from one deep hashing network may not provide the full representation of an image.
In this paper, we propose a novel hashing indexing method, called the Deep Hashing based Fusing Index (DHFI), to generate a more compact hash code which has stronger expression ability and distinction capability.
In our method, we train two different architecture’s deep hashing subnetworks and fuse the hash codes generated by the two subnetworks together to unify images.
Experiments on two real datasets show that our method can outperform state-of-the-art image retrieval applications.
American Psychological Association (APA)
Duan, Lijuan& Zhao, Chongyang& Miao, Jun& Qiao, Yuanhua& Su, Xing. 2017. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval. Applied Computational Intelligence and Soft Computing،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1121481
Modern Language Association (MLA)
Duan, Lijuan…[et al.]. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval. Applied Computational Intelligence and Soft Computing No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1121481
American Medical Association (AMA)
Duan, Lijuan& Zhao, Chongyang& Miao, Jun& Qiao, Yuanhua& Su, Xing. Deep Hashing Based Fusing Index Method for Large-Scale Image Retrieval. Applied Computational Intelligence and Soft Computing. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1121481
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1121481