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In this paper we present an efficient and effective method for visual descriptors hashing based on hierarchical multiple assignment within a k-means framework. The method has been used to address the problem of approximate nearest neighbor (ANN) retrieval, and it has been tested on local and global visual content descriptors, either engineered or learned. The proposed method has been compared to state-of-the-art...
This paper presents a novel method for efficient image retrieval, based on a simple and effective hashing of CNN features and the use of an indexing structure based on Bloom filters. These filters are used as gatekeepers for the database of image features, allowing to avoid to perform a query if the query features are not stored in the database and speeding up the query process, without affecting...
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