Discrete hashing

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August undefined, 2024

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 ... WebNov 15, 2024 · Fig. 1. The framework of SEmantic preserving Asymmetric discrete Hashing (SEAH). It is a two-step hashing approach with two subsections: (1) Training stage 1: SEAH proposes an asymmetric scheme to maintain the similarity of the hash codes and the latent representations more efficiently. (2) Training stage 2: With the hash codes …

Semantic-guided hashing learning for domain adaptive retrieval

WebDiscrete Hashing (SDH) [15] aims to directly optimize the binary hash codes using the discrete cyclic coordinate descend method. Recently, deep learning based hashing … WebDec 2, 2024 · This method operates independently of the number of nodes as the hash function is not dependent on the number of nodes. Here we assume a chain/ring is … shoplane21

Learning Discrete Class-specific Prototypes for Deep Semantic Hashing …

WebSoftware engineer with experience in back-end development. Some of my projects include social networking sites, internal web applications, mobile apps, Java app frameworks, … WebApr 18, 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 information and the classification information are used to learn the hash codes within one stream framework. WebDec 1, 2024 · Firstly, we integrate discrete hash code learning and deep features learning in a unified network framework, which can utilize the semantic supervision to guide … shoplargefamily.com

Nonlinear Robust Discrete Hashing for Cross-Modal Retrieval

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 … 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. Both the pairwise label information and the classification information are used to learn the hash codes within one stream framework. shoplanecoWebJul 31, 2024 · DDSH is the first deep hashing method which can utilize supervised information to directly guide both discrete coding procedure and deep feature learning … shoplatch shrewsbury

"WebFeb 1, 2024 · In our method, discrete strategy in Fig. 1-(c) is used to learn hash codes with binary constraints, which avoids quantization error and get better performance. To … " - Discrete hashing

Discrete hashing

WebMar 24, 2024 · Hashing can facilitate efficient retrieval and storage for large-scale images due to the binary representation. In the real applications, the trade-off between retrieval accuracy and speed is essential for designing a hashing framework, which is reflected by variable hash code lengths. In light of this, the existing hashing methods need to train … WebJul 8, 2024 · The domain adaptive hashing is defined as to learn a binary code matrix B ∈ {− 1,1} r×N and hash function f ( X ), where r is the length of hash codes. For an out-of-sample instance query x_ {t_ {i}}, it can generate hash codes b_ …

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WebMar 7, 2024 · Learning-based hashing algorithms are “hot topics” because they can greatly increase the scale at which existing methods operate. In this paper, we propose a new learning-based hashing method called “fast supervised discrete hashing” (FSDH) based on “supervised discrete hashing” (SDH). Regressing the training examples (or hash … http://papers.neurips.cc/paper/6842-deep-supervised-discrete-hashing.pdf

WebJul 25, 2024 · Discrete Graph Hashing. In NIPS. 3419--3427. Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, and Shih-Fu Chang. 2012. Supervised hashing with kernels. In CVPR. 2074--2081. Xingbo Liu, Xiushan Nie, Wenjun Zeng, Chaoran Cui, Lei Zhu, and Yilong Yin. 2024. Fast Discrete Cross-modal Hashing with Regressing from Semantic … WebApr 28, 2024 · RSDH is a robust discrete hashing method to reduce the noise affection and the quantization error. SDH 1 learns directly the hash code without relaxations. …

WebSep 1, 2024 · Asymmetric Correlation Quantization Hashing for Cross-Modal Retrieval. A novel Asymmetric Correlation Quantization Hashing method that outperforms state-of-the-art methods on several diverse datasets and uses discrete iterative optimization to obtain the unified hash codes across different modalities. WebThe data-dependent hash methods are becoming more and more attractive because they perform well in fast retrieval and storing high-dimensional data. Most existing supervised hashes are centralized, such as supervised discrete hashing (SDH) and supervised discrete hashing with relaxation (SDHR). The SDH algorithm determines the …

WebJun 12, 2015 · We evaluate the proposed approach, dubbed Supervised Discrete Hashing (SDH), on four large image datasets and demonstrate its superiority to the state-of-the …

WebMay 10, 2024 · Some representative deep hashing methods including Deep Pairwise Supervised Hashing (DPSH) [ 15 ], Deep Supervised Discrete Hashing (DSDH) [ 14] and Deep Discrete Supervised Hashing (DDSH) [ 8] integrate deep feature learning and hash code learning into a end-to-end framework and then obtain a great retrieval performance. shoplapiecesWebAug 25, 2024 · The proposed Deep Balanced Discrete Hashing (DBDH) is a deep hashing method. DBDH uses supervised information to guide both deep feature learning process and the discrete hashing process. 2. The proposed method enables the network to learn discrete hash code directly. shoplaza incWebJul 1, 2024 · In this paper, we propose a novel method, called column sampling based discrete supervised hashing (COSDISH), to directly learn the discrete hashing code from semantic information. COSDISH is an ... shoplawnboy.comWebIn this article, we propose distributed supervised discrete hashing algorithm with relaxation (DSDHR) based on SDHR. The SDHR algorithm is introduced into the distributed … shoplar sinopWebAug 4, 2024 · ALECH decomposes hash learning into two steps, hash codes learning and hash functions learning. For hash codes learning, the high-order semantic label correlations are adaptively exploited to guide the latent feature learning, while simultaneously generating the binary codes in a discrete manner. shoplatch shrewsbury mapWebApr 22, 2024 · Deep discrete supervised hashing [41] also used Eq. (1) to conduct image retrieval, but it employed the hyperbolic tangent function instead of a hash representation, which is actually a relaxation strategy. In fact, most deep learning strategies utilized this relaxation strategy. shoplauer.com reviewsWebOct 11, 2024 · In this paper, we propose a novel Discrete Fusion Adversarial Hashing (DFAH) approach for cross-modal retrieval. Our model consists of three modules: the Modality-Specific Feature Extractor, the Fusion Learner and the Modal Discriminator. shoplc bali bracelets