In this paper, a deep framework is used to learn similarity-preserving hash codes in a point-wised manner, aiming at large-scale image retrieval. In practice, ...
Similarity-preserving hashing has become the mainstream of approximate nearest neighbor (ANN) search for large-scale image retrieval. Recent research shows that ...
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Jul 10, 2023 · Deep Neighborhood Structure-Preserving Hashing for Large-Scale Image Retrieval. Abstract: Deep hashing integrates the advantages of deep ...
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Jun 22, 2021 · Deep hashing models have been proposed as an ef- ficient method for large-scale similarity search. How- ever, most existing deep hashing ...
This archi- tecture accepts input images in a pairwise form (xi, xj,sij) and processes them through the deep hashing pipeline: (1) a sub-network with multiple ...
Jun 19, 2018 · In this paper, a new Deep Hashing with Top Similarity Preserving (DHTSP) method is proposed to optimize the quality of hash codes for image ...
A new Deep Hashing with Top Similarity Preserving (DHTSP) method is proposed to optimize the quality of hash codes for image retrieval by utilizing AlexNet ...
Apr 18, 2024 · In this paper, we propose a novel end-to-end deep hashing method based on the similarities of binary codes, dubbed CSDH (Code Similarity-based ...
Specifically, ADSH only learns hash function for query points, while DAPH jointly trains two different models to learn pairwise similarity-preserving codes. The ...
Similarity-preserving Hashing Based on Deep Neural Networks for Large-scale Image Retrieval. J. of Visual Communication and Image Representation.