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• W2007477183 abstract "This paper addresses the construction of a short-vector (128D) image representation for large-scale image and particular object retrieval. In particular, the method of joint dimensionality reduction of multiple vocabularies is considered. We study a variety of vocabulary generation techniques: different k-means initializations, different descriptor transformations, different measurement regions for descriptor extraction. Our extensive evaluation shows that different combinations of vocabularies, each partitioning the descriptor space in a different yet complementary manner, results in a significant performance improvement, which exceeds the state-of-the-art." @default.
• W2007477183 created "2016-06-24" @default.
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• W2007477183 date "2015-06-22" @default.
• W2007477183 modified "2023-09-30" @default.
• W2007477183 title "Multiple Measurements and Joint Dimensionality Reduction for Large Scale Image Search with Short Vectors" @default.
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• W2007477183 doi "https://doi.org/10.1145/2671188.2749366" @default.
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