2024 Supervised discrete hashing

Supervised discrete hashing

Author: lpqa

August undefined, 2024

WebIn this article, we propose a novel asymmetric hashing method, called Deep Uncoupled Discrete Hashing (DUDH), for large-scale approximate nearest neighbor search. Instead of directly preserving the similarity between the query and database, DUDH first exploits a small similarity-transfer image set to transfer the underlying semantic structures ... WebDec 1, 2024 · Abstract. Hashing has been widely used for large-scale search due to its low storage cost and fast query speed. By using supervised information, supervised hashing can significantly outperform unsupervised hashing. Recently, discrete supervised hashing and feature learning based deep hashing are two representative progresses in supervised …

Asymmetric Deep Supervised Hashing - Association for the …

WebMay 31, 2024 · In this paper, we develop a deep supervised discrete hashing algorithm based on the assumption that the learned binary codes should be ideal for classification. … WebIn this paper, we propose a supervised discrete-based cross-modal hashing method, named Scalable Discriminative Discrete Hashing (SDDH), for cross-modal retrieval, where 1) the discrete hash codes are directly obtained by multi-modal features and semantic labels so that the quantization errors are dramatically reduced, and 2) the discrete hash ... long kitchen lighting fixture

SDMCH: Supervised Discrete Manifold-Embedded Cross …

WebMar 7, 2024 · In this paper, we propose a new learning-based hashing method called “fast supervised discrete hashing” (FSDH) based on “supervised discrete hashing” (SDH). … WebApr 14, 2024 · In this paper, we present a novel supervised cross-modal hashing framework, namely Scalable disCRete mATrix faCtorization Hashing (SCRATCH). First, it utilizes collective matrix factorization on original features together with label semantic embedding, to learn the latent representations in a shared latent space. Thereafter, it generates binary … WebSource code for paper "Deep Supervised Discrete Hashing" on NeurIPS-2024 - GitHub - TreezzZ/DSDH_PyTorch: Source code for paper "Deep Supervised Discrete Hashing" on NeurIPS-2024 long kitchen matches

Distributed Supervised Discrete Hashing With Relaxation

Deep Discrete Supervised Hashing IEEE Journals & Magazine - IEEE X…

WebHashing has been widely used for large-scale search due to its low storage cost and fast query speed. By using supervised information, supervised hashing can significantly … WebHashing has been widely used for large-scale search due to its low storage cost and fast query speed. By using supervised information, supervised hashing can significantly outperform unsupervised hashing. Recently, discrete supervised hashing and feature learning based deep hashing are two represent … long kitchen mats washableWebIn this paper, we develop a deep supervised discrete hashing algorithm based on the assumption that the learned binary codes should be ideal for classification. Both the … long kitchen prep table

"WebApr 22, 2024 · Supervised discrete cross-modal hashing based on kernel discriminant analysis Pattern Recognit. (2024) ZhongF. et al. Deep discrete cross-modal hashing for cross-media retrieval Pattern Recognit. (2024) FangY. et al. Unsupervised cross-modal retrieval via multi-modal graph regularized smooth matrix factorization hashing Knowl. … " - Supervised discrete hashing

Supervised discrete hashing

WebTherefore, Equation (3) is a reasonable and effective way to solve the discrete hashing optimization in neural network, which will be further demonstrated with experiments later. 2.2 Back propagating the coding message with a new hash layer In section 2.1 we have discussed why we choose (3) to deal with the discrete optimization in neural WebApr 7, 2024 · In this paper, we propose a novel learning-based hashing method called "Supervised Discrete Hashing with Relaxation" (SDHR) based on "Supervised Discrete …

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Webcross-modal hashing method, named Supervised Discrete Manifold-Embedded Cross-Modal Hash-ing (SDMCH). It can not only exploit the non-linear manifold structure of data and construct the correlation among heterogeneous multiple modal-ities, but also fully utilize the semantic informa-tion. Moreover, the hash codes can be generated WebSupervised Discrete Hashing. In Proceedings of the International Conference on Computer Vision and Pattern Recognition. 37--45. Jingkuan Song, Yang Yang, Yi Yang, Zi Huang, and Heng Tao Shen. 2013. Inter-Media Hashing for Large …

WebBesides, the hashing learning procedure is efficiently supervised by the pair-wise semantic matrix to enhance the discriminative capability. It could successfully avoid the challenging symmetric semantic matrix factorization and O ( n2) storage cost of semantic matrix. WebApr 12, 2024 · SVFormer: Semi-supervised Video Transformer for Action Recognition ... Deep Hashing with Minimal-Distance-Separated Hash Centers Liangdao Wang · Yan Pan · …

WebFeb 2, 2024 · However, most existing deep supervised hashing methods adopt a symmetric strategy to learn one deep hash function for both query points and database (retrieval) points. The training of these symmetric deep supervised hashing methods is typically time-consuming, which makes them hard to effectively utilize the supervised information for … WebFeb 17, 2024 · A discrete hash optimization approach is developed to learn the binary codes without relaxation, avoiding the large quantization loss. The proposed hash function …

WebApr 22, 2024 · In this article, we propose distributed supervised discrete hashing algorithm with relaxation (DSDHR) based on SDHR. The SDHR algorithm is introduced into the distributed network. In this framework, all nodes share a centralized hash learning model.

WebSep 1, 2024 · With limited label available, this paper presents a novel S emi-S upervised D iscrete H ashing (SSDH) for efficient cross-modal retrieval. In contrast to most semi-supervised cross-modal hashing ... long kitchen plinthsWebApr 12, 2024 · SVFormer: Semi-supervised Video Transformer for Action Recognition ... Deep Hashing with Minimal-Distance-Separated Hash Centers Liangdao Wang · Yan Pan · Cong Liu · Hanjiang Lai · Jian Yin · Ye Liu ... Delving into Discrete Normalizing Flows on SO(3) Manifold for Probabilistic Rotation Modeling ... long kitchen picturesWebNov 12, 2015 · In this paper, we propose a novel deep hashing method, called deep pairwise-supervised hashing (DPSH), to perform simultaneous feature learning and hash-code learning for applications with pairwise labels. Experiments on real datasets show that our DPSH method can outperform other methods to achieve the state-of-the-art performance … long kitchen rugs williams sonomaWebDiscrete Binary Hashing Towards Efficient Fashion Recommendation. Authors: Luyao Liu ... hooverville fontWebAsymmetric Deep Supervised Hashing Qing-Yuan Jiang, Wu-Jun Li National Key Laboratory for Novel Software Technology ... 2012), discrete graph hashing (DGH) (Liu et al. 2014), scal-able graph hashing (SGH) (Jiang and Li 2015) and ordinal embedding hashing (OEH) (Liu et al. 2016b). Unsupervised hooverville foodWebOct 15, 2024 · Supervised linear hashing can compress high-dimensional data into compact binary codes owing to its efficiency. Generally, the relation between label and hash codes is widely used in the existing ... hooverville grapes of wrathWebIn this paper, we develop a deep supervised discrete hashing algorithm based on the assumption that the learned binary codes should be ideal for classification. Both the pairwise label information and the classification information are used to learn the hash codes within one stream framework. We constrain the outputs of the last layer to be ... long kitchen renovation