Supervised Matrix Factorization Hashing With Quantitative Loss for Image-Text Search

Supervised Matrix Factorization Hashing With Quantitative Loss for Image-Text Search

Image-text hashing approaches have been widely applied in large-scale similarity search applications due to their efficiency in both search speed and storage efficiency. Most recent supervised hashing approaches learn a hash function by constructing a pairwise similarity matrix or directly learning...

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Bibliographic Details
Main Authors: Huan Zhao, Song Wang, Xiaolin She, Chenghui Su
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Image-text search
supervised hashing
hash function
hash codes
quantitative loss function
Online Access:https://ieeexplore.ieee.org/document/9103528/

Internet

https://ieeexplore.ieee.org/document/9103528/

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