Results 1 to 10 of about 1,457 (180)
Deep supervised hashing for gait retrieval [version 2; peer review: 2 approved] [PDF]
F1000Research, 2022 Background: Gait recognition is perceived as the most promising biometric approach for future decades especially because of its efficient applicability in surveillance systems.
Shohel Sayeed, Pa Pa Min, Thian Song Ong
doaj +5 more sources
Distributed Fast Supervised Discrete Hashing [PDF]
IEEE Access, 2019 Hash-based learning has attracted considerable attention due to its fast retrieval speed and low computational cost for the large-scale database. Compared with unsupervised hashing, supervised hashing achieves higher retrieval accuracy generally by ...
Zhifeng Liu, Feng Chen, Shukai Duan
doaj +2 more sources
Enhanced Image Retrieval Using Multiscale Deep Feature Fusion in Supervised Hashing [PDF]
Journal of ImagingIn recent years, deep-network-based hashing has gained prominence in image retrieval for its ability to generate compact and efficient binary representations.
Amina Belalia +2 more
doaj +2 more sources
Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval [PDF]
EntropyDeep hashing technology, known for its low-cost storage and rapid retrieval, has become a focal point in cross-modal retrieval research as multimodal data continue to grow.
Qiang Zou +3 more
doaj +2 more sources
Online Semi-supervised Cross-modal Hashing Based on Anchor Graph Classification [PDF]
Jisuanji kexue, 2023 In recent years,hashing algorithm have been widely concerned in efficient cross-modal retrieval of large-scale multimedia data due to small storage costs and high retrieval speed.Most of the existing cross-modal hashing algorithms are supervised or ...
QIN Liang, XIE Liang, CHEN Shengshuang, XU Haijiao
doaj +1 more source
Weakly-Supervised Online Hashing [PDF]
2021 IEEE International Conference on Multimedia and Expo (ICME), 2021 Accepted by ICME ...
Zhan, Yu-Wei +5 more
openaire +2 more sources
Distributed Supervised Discrete Hashing With Relaxation
IEEE Access, 2021 The 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
Rui Hu, Ming Ye, Changyou Ma, Feng Chen
doaj +1 more source
Fast Supervised Discrete Hashing [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018 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).
Jie Gui +4 more
openaire +3 more sources
Deep Discrete Supervised Hashing [PDF]
IEEE Transactions on Image Processing, 2018 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 deep hashing are two representative progresses in supervised hashing. On one hand, hashing is essentially a
Qing-Yuan Jiang, Xue Cui, Wu-Jun Li
openaire +3 more sources
Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing [PDF]
, 2021 Semantic hashing is an emerging technique for large-scale similarity search based on representing high-dimensional data using similarity-preserving binary codes used for efficient indexing and search. It has recently been shown that variational autoencoders, with Bernoulli latent representations parametrized by neural nets, can be successfully trained ...
Ricardo NĖanculef +4 more
openaire +3 more sources