Junshan Tan1, Rong Duan1, Jiaohua Qin1, *, Xuyu Xiang1, Yun Tan1
CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 675-689, 2020, DOI:10.32604/cmc.2020.07730
Abstract Hashing technology has the advantages of reducing data storage and improving
the efficiency of the learning system, making it more and more widely used in image
retrieval. Multi-view data describes image information more comprehensively than
traditional methods using a single-view. How to use hashing to combine multi-view data
for image retrieval is still a challenge. In this paper, a multi-view fusion hashing method
based on RKCCA (Random Kernel Canonical Correlation Analysis) is proposed. In order
to describe image content more accurately, we use deep learning dense convolutional
network feature DenseNet to construct multi-view by combining GIST feature or
BoW_SIFT (Bag-of-Words… More >
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