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The ability of fast similarity search in a large-scale dataset is of great importance to many multimedia applications. Semantic hashing is a promising way to accelerate similarity search, which designs compact binary codes for a large number of images so that semantically similar images are mapped to close codes. Retrieving similar neighbors is then simply accomplished by retrieving images that have codes within a small Hamming distance of the code of the query. Among various hashingdoi:10.1109/tmm.2012.2199970 fatcat:eyqkocabgvfejcmihr6ywadcum