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- W2017299852 abstract "In allusion to similarity calculation difficulty caused by high maintenance of image data, this paper introduces sparse principal component algorithm to figure out embedded subspace after dimensionality reduction of image visual words on the basis of traditional spectral hashing image index method so that image high-dimension index results can be explained overall. This method is called sparse spectral hashing index. The experiments demonstrate the method proposed in this paper superior to LSH, RBM and spectral hashing index methods." @default.
- W2017299852 created "2016-06-24" @default.
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- W2017299852 date "2014-12-01" @default.
- W2017299852 modified "2023-09-22" @default.
- W2017299852 title "SSH: Image Index Based on Sparse Spectral Hashing" @default.
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- W2017299852 doi "https://doi.org/10.1109/cse.2014.349" @default.
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