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- W2153901642 abstract "One key challenge in content-based image retrieval (CBIR) is to develop a fast solution for indexing high-dimensional image contents, which is crucial to building large-scale CBIR systems. In this paper, we propose a scalable content-based image retrieval scheme using locality-sensitive hashing (LSH), and conduct extensive evaluations on a large image testbed of a half million images. To the best of our knowledge, there is less comprehensive study on large-scale CBIR evaluation with a half million images. Our empirical results show that our proposed solution is able to scale for hundreds of thousands of images, which is promising for building Web-scale CBIR systems." @default.
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- W2153901642 date "2007-07-01" @default.
- W2153901642 modified "2023-09-27" @default.
- W2153901642 title "An Empirical Study on Large-Scale Content-Based Image Retrieval" @default.
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- W2153901642 doi "https://doi.org/10.1109/icme.2007.4285123" @default.
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