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International Journal of Computer Vision
Article . 2019 . Peer-reviewed
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https://doi.org/10.1109/cvpr.2...
Article . 2016 . Peer-reviewed
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Claim

Deep Supervised Hashing for Fast Image Retrieval

Deep supervised hashing for fast image retrieval
descriptionPublicationkeyboard_double_arrow_right Article , Conference object 01 Jun 2016Publisher:IEEEJournal:2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Authors: Haomiao Liu; Ruiping Wang 0001; Shiguang Shan; Xilin Chen 0001;

doi: 10.1109/cvpr.2016.227 , 10.1007/s11263-019-01174-4

Deep Supervised Hashing for Fast Image Retrieval

Abstract

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Keywords

triplet ranking loss, Information storage and retrieval of data, Computing methodologies for image processing, contrastive loss, image retrieval, hashing, Artificial neural networks and deep learning, convolutional network

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 618
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Top 0.1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 0.1%
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
618
Top 0.1%
Top 0.1%
Top 0.1%
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