WebSep 19, 2024 · Recently, supervised cross-modal hashing has attracted much attention and achieved promising performance. To learn hash functions and binary codes, most methods globally exploit the supervised information, for example, preserving an at-least-one pairwise similarity into hash codes or reconstructing the label matrix with binary codes. WebDec 27, 2024 · Unsupervised multi-modal hashing has received considerable attention in large-scale multimedia retrieval areas since its low storage and high search speed. Existing unsupervised multi-modal hashing methods usually aim to mine the complementary information and the structural information for different modalities and preserve them in …
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WebAs an important branch of hashing methods, multi-view hashing takes advantages of multiple features from different views for binary hash learning. However, existing multi-view hashing methods are either based on shallow models which fail to fully capture the intrinsic correlations of heterogeneous views, or unsupervised deep models which suffer ... WebOct 1, 2024 · In recent years, discrete supervised hashing methods have attracted increasing attention because of their high retrieval efficiency and precision. However, in … property for rent in lahinch co clare
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WebApr 19, 2024 · Unsupervised Generative Adversarial Cross-modal Hashing (UGACH) [31] proposed to use a generative adversarial network to learn better underlying features from multiple modalities. WebNov 17, 2024 · Hashing is an effective technique to solve large-scale data storage problem and achieve efficient retrieval, and it is also a core technology to promote the intelligent development of the new infrastructure construction. In most practical situations, label information is unavailable, and creating manual annotations is a time-consuming and … WebDec 1, 2024 · An end-to-end deep hashing method called deep multiscale fusion hashing (DMFH) for cross-modal retrieval that can learn common hash codes directly without a relaxation, thereby avoiding a loss in accuracy during hash learning. 18 Multi-Task Consistency-Preserving Adversarial Hashing for Cross-Modal Retrieval lady a tour tickets