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- W2166625785 abstract "In this paper, we propose a new approach for similarity matching in image retrieval based on approximate query processing in a hierarchical SOM. We first map the high dimensional input vectors to a low dimensional grid by a local membership function which preserves the relationships between the input vectors and their neighboring weight vectors. Then, we use a hierarchical tree to reduce the computation cost for finding the best match unit. Finally, we retrieve the k nearest neighbors of the query vector by an approximate query processing approach. The experiments show that the proposed approach works well on both synthetic datasets and image databases." @default.
- W2166625785 created "2016-06-24" @default.
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- W2166625785 date "2006-01-01" @default.
- W2166625785 modified "2023-10-18" @default.
- W2166625785 title "Approximate query processing for efficient content-based image retrieval based on a hierarchical SOM" @default.
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- W2166625785 doi "https://doi.org/10.1109/ijcnn.2006.246924" @default.
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