Results 11 to 20 of about 10,164 (194)

Asymmetric Deep Supervised Hashing

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
Hashing has been widely used for large-scale approximate nearest neighbor search because of its storage and search efficiency. Recent work has found that deep supervised hashing can significantly outperform non-deep supervised hashing in many applications. However, most existing deep supervised hashing methods adopt a symmetric strategy
Jiang, Qing-Yuan, Li, Wu-Jun
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Deep Discrete Hashing with Self-supervised Pairwise Labels [PDF]

, 2017
Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature representation and end-to-end learning framework. However, the most striking successes in deep hashing have
Song, Jingkuan, He, Tao, Fan, Hangbo, Gao, Lianli   +3 more
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Fusion-Supervised Deep Cross-Modal Hashing [PDF]

2019 IEEE International Conference on Multimedia and Expo (ICME), 2019
Deep hashing has recently received attention in cross-modal retrieval for its impressive advantages. However, existing hashing methods for cross-modal retrieval cannot fully capture the heterogeneous multi-modal correlation and exploit the semantic information.
Wang, Li, Zhu, Lei, Yu, En, Sun, Jiande, Zhang, Huaxiang   +4 more
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User privacy prevention model using supervised federated learning‐based block chain approach for internet of Medical Things

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in‐build supervised learning‐based smart contract is designed to improvise ...
Chandramohan Dhasarathan, Mohammad Kamrul Hasan, Shayla Islam, Salwani Abdullah, Shailesh Khapre, Dalbir Singh, Abdulaziz A. Alsulami, Ali Alqahtani   +7 more
wiley   +1 more source

IPDH: An Improved Pairwise-Based Deep Hashing Method for Large-Scale Image Retrieval

IEEE Access, 2020
Hashing technique has been extensively utilized in approximate nearest neighbor (ANN) search for large-scale image retrieval by virtue of its storage simplicity and computational efficiency. Recently, many researches show that hashing methods based.
Wei Yao, Feifei Lee, Lu Chen, Chaowei Lin, Shuai Yang, Hanqing Chen, Qiu Chen   +6 more
doaj   +1 more source

Contrastive Self-Supervised Hashing With Dual Pseudo Agreement

IEEE Access, 2020
Recently, unsupervised deep hashing has attracted increasing attention, mainly because of its potential ability to learn binary codes without identity annotations.
Yang Li, Yapeng Wang, Zhuang Miao, Jiabao Wang, Rui Zhang   +4 more
doaj   +1 more source

Deep Contrastive Self-Supervised Hashing for Remote Sensing Image Retrieval

Remote Sensing, 2022
Hashing has been widely used for large-scale remote sensing image retrieval due to its outstanding advantages in storage and search speed. Recently, deep hashing methods, which produce discriminative hash codes by building end-to-end deep convolutional ...
Xiaoyan Tan, Yun Zou, Ziyang Guo, Ke Zhou, Qiangqiang Yuan   +4 more
doaj   +1 more source

Deep Supervised Hashing with Nonlinear Projections [PDF]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Hashing has attracted broad research interests in large scale image retrieval due to its high search speed and efficient storage. Recently, many deep hashing methods have been proposed to perform simultaneous nonlinear feature learning and hash projection learning, which have shown superior performance compared to hand-crafted feature based hashing ...
Sen Su, Gang Chen, Xiang Cheng, Rong Bi
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Deep Hashing Based on Class-Discriminated Neighborhood Embedding

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS) owing to their prominent capabilities for capturing the semantics from complex RS scenes and generating the associated hash codes in an end-to-
Jian Kang, Ruben Fernandez-Beltran, Zhen Ye, Xiaohua Tong, Antonio Plaza   +4 more
doaj   +1 more source

Deep supervised hashing using symmetric relative entropy [PDF]

Pattern Recognition Letters, 2019
By virtue of their simplicity and efficiency, hashing algorithms have achieved significant success on large-scale approximate nearest neighbor search. Recently, many deep neural network based hashing methods have been proposed to improve the search accuracy by simultaneously learning both the feature representation and the binary hash functions.
Xueni Zhang, Lei Zhou, Xiao Bai, Xiushu Luan, Jie Luo, Edwin R. Hancock   +5 more
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