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Discrete hashing with multiple supervision

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 http://www.nlm.medscape.idmu.unboundmedicine.unboundmedicine.com/medline/citation/30640611/Discrete_Hashing_with_Multiple_Supervision_

Discrete Hashing With Multiple Supervision - IEEE Xplore

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. WebApr 21, 2024 · Discrete hashing with multiple supervision. IEEE Transactions on Image Processing 28, 6 (2024), 2962–2975. Google Scholar Cross Ref; Chao Ma, Chen Gong, Xiang Li, Xiaolin Huang, Wei Liu, and Jie Yang. 2024. Toward making unsupervised graph hashing discriminative. IEEE Transactions on Cybernetics 22, 3 (2024), 760–774. hakasalmen huvila https://swflcpa.net

PRIME PubMed Discrete Hashing with Multiple Supervision

WebSep 1, 2024 · In this paper, we develop a general deep supervised discrete hashing framework based on the assumption that the learned binary codes should be ideal for classification. Both the similarity... WebMar 24, 2024 · To address the aforementioned issues, we propose a new model, known as supervised discrete multiple-length hashing (SDMLH), to simultaneously learn hash … WebOct 11, 2024 · During the unified hash codes learning, we design an efficient discrete optimization method based on column-sampling and this optimization method can … haka putzmittel test

High-order nonlocal Hashing for unsupervised cross-modal retrieval ...

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Discrete hashing with multiple supervision

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WebMar 21, 2024 · To simultaneously support multiple multimedia retrieval tasks, multiple different hashing models should be equipped in a multimedia retrieval system. This … WebOct 1, 2024 · In recent years, discrete supervised hashing methods have attracted increasing attention because of their high retrieval efficiency and precision. However, in …

Discrete hashing with multiple supervision

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WebSupervised cross-modal hashing has gained a lot of attention recently. However, most existing methods learn binary codes or hash functions in a batch-based scheme, which is inefficient in an online scenario, i.e., data points come in a streaming fashion. WebMar 24, 2024 · To address the aforementioned issues, we propose a new model, known as supervised discrete multiple-length hashing (SDMLH), to simultaneously learn hash codes with multiple lengths. In this proposed SDMLH method, three types of information are respectively derived, from the hash codes with different lengths. The original …

WebExtensive experiments on three widely-used datasets demonstrate the superior performance of HSCH compared with several state-of-the-art cross-modal hashing approaches. References Cong Bai, Chao Zeng, Qing Ma, Jinglin Zhang, and Shengyong Chen. 2024. Deep adversarial discrete hashing for cross-modal retrieval. 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.

WebTo address these limitations, in this paper, we present a novel hashing method, named Discrete Hashing with Multiple Supervision (MSDH). MSDH supervises the hash … WebOct 25, 2024 · To embedding the label supervision, Online Latent Semantic Hashing (OLSH) maps discrete tags to a continuous latent semantic space, while updating hash functions based on only newly arriving multimedia data points. This approach has produced promising retrieval performances to sequentially process the streaming data points, but …

WebSep 23, 2024 · Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is based on the...

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 … haka quotesWebMar 21, 2024 · To simultaneously support multiple multimedia retrieval tasks, multiple different hashing models should be equipped in a multimedia retrieval system. This paper proposes a Structured Multi-Modal Hashing (SMMH) method, which can learn only a hash model for multiple multimedia retrieval tasks. pisa harmarvilleWebAs 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 ... pisa hermosilloWebFeb 27, 2024 · In light of the ability to enable efficient storage and fast query for big data, hashing techniques for cross-modal search have aroused extensive attention. Despite the great success achieved, unsupervised cross-modal hashing still suffers from lacking reliable similarity supervision and struggles with handling the heterogeneity issue between … pis ailtonWebThus, we propose the Deep Discrete Cross-Modal Hashing with Multiple Supervision (DDCH ms) to further enhance the semantic consistency of heterogeneous modalities. It improves the performance of semantic information retrieval with the joint supervision of instance-pairwise, instance-labeled and class-wise similarities. hakasen leipomo itsenäisyydenkatu tampereWebJul 14, 2024 · Deep Discrete Cross-Modal Hashing with Multiple Supervision Neurocomputing, Volume 486, 2024, pp. 215-224 Show abstract Liuyin Lin received her B.S. degree in Computer Science and Technology from … pisai animalWebJan 1, 2024 · Recently, discrete supervised hashing and deep hashing are two representative progresses in supervised hashing. On one hand, hashing is essentially a … häkärinteet oy