Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Shanhua Zhan"'
Autor:
Shanhua ZHAN, Shaorong HUANG
Publikováno v:
Dianxin kexue, Vol 34, Pp 65-70 (2018)
The RFID system is made up of three parts:tags,readers and databases.The information between tags and readers are transmitted through wireless channel,which is easy to be intercepted by attackers.A two-way authentication protocol based on word Synthe
Externí odkaz:
https://doaj.org/article/2d8b0f23a157411b9f950dcecdd8a13f
Publikováno v:
Mathematics, Vol 7, Iss 10, p 976 (2019)
In this paper, we propose a separable reversible data hiding method in encrypted image (RDHEI) based on two-dimensional permutation and exploiting modification direction (EMD). The content owner uses two-dimensional permutation to encrypt original im
Externí odkaz:
https://doaj.org/article/cb2cf7e39c0f4020aabb736053c1d01e
Publikováno v:
Information Sciences. 584:89-110
Vacating room after encryption (VRAE) is a popular framework of reversible data hiding for encrypted images (RDHEI). Most VRAE based RDHEI methods do not make a desirable payload. To address this issue, this paper proposes a novel data hiding techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d75766856a4ab045215ac6f4c5b9c9d
https://doi.org/10.1016/j.ins.2021.10.050
https://doi.org/10.1016/j.ins.2021.10.050
Publikováno v:
International Journal of Machine Learning and Cybernetics. 12:2843-2857
In this paper, we focus on how to boost the semi-supervised classification performance by exploring the multi-view graph learning. The key of multi-view graph learning is to learn a discriminative and informative graph from the multiple input graphs.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16527732dd36cad79990b283d1b0d935
https://doi.org/10.1007/s13042-021-01370-0
https://doi.org/10.1007/s13042-021-01370-0
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 30:760-770
In this paper, a novel least square regression method, named group low-rank representation-based discriminant linear regression (GLRRDLR), is proposed for multi-class classification. Unlike the conventional linear regression methods, the proposed met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::022d593e5e99b4dc2852189d4f9c0fd2
https://doi.org/10.1109/tcsvt.2019.2897072
https://doi.org/10.1109/tcsvt.2019.2897072
Publikováno v:
IEEE Transactions on Image Processing. 29:2820-2833
Subspace learning based transfer learning methods commonly find a common subspace where the discrepancy of the source and target domains is reduced. The final classification is also performed in such subspace. However, the minimum discrepancy does no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5e7563e136bd1bb74b55633da50f258
https://doi.org/10.1109/tip.2019.2952739
https://doi.org/10.1109/tip.2019.2952739
Publikováno v:
IEEE Transactions on Cybernetics. 49:1279-1291
Preserving global and local structures during projection learning is very important for feature extraction. Although various methods have been proposed for this goal, they commonly introduce an extra graph regularization term and the corresponding re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a244e815088f3aba2dd82be14c43505
https://doi.org/10.1109/tcyb.2018.2799862
https://doi.org/10.1109/tcyb.2018.2799862
Publikováno v:
Neural Networks. 109:56-66
Manifold based feature extraction has been proved to be an effective technique in dealing with the unsupervised classification tasks. However, most of the existing works cannot guarantee the global optimum of the learned projection, and they are sens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::904f38f99fbc8d2414e5336ab1e052b8
https://doi.org/10.1016/j.neunet.2018.10.001
https://doi.org/10.1016/j.neunet.2018.10.001
Publikováno v:
Heliyon, Vol 10, Iss 16, Pp e35889- (2024)
The GM(1,1) model's prediction accuracy is significantly influenced by the accuracy of background value estimation. The traditional trapezoidal background value can only be applied to a specific data sequence. Therefore, this study proposes a GM(1,1)
Externí odkaz:
https://doaj.org/article/52972c969e7b4762875fb0d8fdcfb01f
Autor:
Shanhua Zhan
Publikováno v:
2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE).
Dimensionality reduction plays an important role in pattern classification. In this paper, a robust unsupervised dimensionality reduction method termed robust sparse locality preserving projection with adaptive graph embedding is proposed. Specifical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b776afad797c09dd23cef0a0feaa4d64
https://doi.org/10.1109/icmcce51767.2020.00440
https://doi.org/10.1109/icmcce51767.2020.00440