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TDHPPIR : an efficient deep hashing based privacy-preserving image retrieval method
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Zhang, Chengyuan, Zhu, Lei, Zhang, Shichao and Yu, Weiren (2020) TDHPPIR : an efficient deep hashing based privacy-preserving image retrieval method. Neurocomputing , 406 . pp. 386-398. doi:10.1016/j.neucom.2019.11.119 ISSN 0925-2312.
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Official URL: http://dx.doi.org/10.1016/j.neucom.2019.11.119
Abstract
With the rapid development of multimedia techniques, mobile Internet and cloud computing, large-scale image retrieval service has become a necessity in our daily life. To overcome the challenges of privacy-preserving and data security during the image retrieval, we propose a novel deep hashing based privacy-preserving image retrieval method named TDHPPIR that can generate high quality hash codes of image and provide an efficient index structure for fast image retrieval in a security manner in cloud. A triplet Deep CNN structure model is introduced to learn deep visual representations and hash codes of images simultaneously, which can generate higher quality hash codes than the traditional way that mainly utilizes hand-crafted features. Besides, A novel hierachical bit-scalable hash codes based S-Tree, named H2S-Tree, is developed to increase the search efficiency. Comprehensive experiments on four benchmarks show that our method can combat the state-of-the-arts in both aspects of accuracy and efficiency.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||
Journal or Publication Title: | Neurocomputing | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 0925-2312 | ||||||||
Official Date: | 17 September 2020 | ||||||||
Dates: |
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Volume: | 406 | ||||||||
Page Range: | pp. 386-398 | ||||||||
DOI: | 10.1016/j.neucom.2019.11.119 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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