Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Jiu-Lun Fan"'
Publikováno v:
Tongxin xuebao, Vol 38, Pp 121-127 (2017)
In the cloud environment for data storage,the use of secure network coding technology can be a good solution to the data privacy and reliability issues.However,each coding block usually has a high correlation after network coding,very few updates to
Externí odkaz:
https://doaj.org/article/ddb7c23873b048959c5721561b350a5f
Publikováno v:
网络与信息安全学报, Vol 2, Pp 1-10 (2016)
The emergence of quantum algorithms have threatened the security of digital signature algorithms widely used currently,most of which based on some hard problems in number theory.The digital signature algorithms based on error correcting codes,which c
Externí odkaz:
https://doaj.org/article/957af59c776b4db785e0ec09501e318d
Publikováno v:
网络与信息安全学报, Vol 2, Pp 1-7 (2016)
The problems of information security demands for professional talents and existing curriculum system setting of information security major were analyzed.A modular and hierarchical curriculum system construction scheme of information security was give
Externí odkaz:
https://doaj.org/article/f51028e8212e446b8b89094c46afc07a
Publikováno v:
IEEE Access, Vol 7, Pp 21465-21481 (2019)
In order to reduce the computational complexity of multi-objective evolutionary optimization-based clustering algorithms, a Kriging-assisted reference vector guided multi-objective robust spatial fuzzy clustering algorithm (KRV-MRSFC) is proposed and
Externí odkaz:
https://doaj.org/article/30593ee771474fc2b7a885fcd21e0fab
Publikováno v:
2022 14th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2eb8a83b3f17591262ee9c5a7878a23b
https://doi.org/10.1109/icmtma54903.2022.00119
https://doi.org/10.1109/icmtma54903.2022.00119
Adaptive Kaniadakis entropy thresholding segmentation algorithm based on particle swarm optimization
Autor:
Bo Lei, Jiu-lun Fan
Publikováno v:
Soft Computing. 24:7305-7318
Kaniadakis entropy is a kind of generalized entropy based on the $$ \kappa $$ probability distribution, which has a good ability to deal with the distribution of long tail. The image thresholding algorithm based on Kaniadakis entropy can effectively
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c82a5e2eba208d48ade0151c7e540106
https://doi.org/10.1007/s00500-019-04351-2
https://doi.org/10.1007/s00500-019-04351-2
Publikováno v:
IEEE Access, Vol 7, Pp 21465-21481 (2019)
In order to reduce the computational complexity of multi-objective evolutionary optimization-based clustering algorithms, a Kriging-assisted reference vector guided multi-objective robust spatial fuzzy clustering algorithm (KRV-MRSFC) is proposed and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ca202a8f2d82d1546e84f2ef7c249e4
https://ieeexplore.ieee.org/document/8635556/
https://ieeexplore.ieee.org/document/8635556/
Publikováno v:
ICMIP
Crime scene investigation (CSI) image retrieval plays an important role in police case solving. In order to relieve the problem of over-fitting in the training of Convolutional Neural Network (CNN) model due to the limited number of CSI images, this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cde891834161ba5d055b3f6e4f96213
https://doi.org/10.1145/3195588.3195605
https://doi.org/10.1145/3195588.3195605
Publikováno v:
Neurocomputing. 168:994-1010
Fuzzy partition entropy-based method is an effective way for image segmentation. In this paper a segmentation method based on a weak fuzzy partition is presented. Firstly, we propose a method to construct generalized fuzzy complement, and moreover co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fee76f8ca750a0fc38303a0e8e01ddb
https://doi.org/10.1016/j.neucom.2015.05.025
https://doi.org/10.1016/j.neucom.2015.05.025
Publikováno v:
Neurocomputing. 134:20-29
In view of local feature weighting hard c-means (LWHCM) clustering algorithm sensitive to noise, based on a non-Euclidean metric, a robust local feature weighting hard c-means (RLWHCM) clustering algorithm is presented. RLWHCM is a natural, effective
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed66f18343e8182cd7a52e9b9bb1aa45
https://doi.org/10.1016/j.neucom.2012.12.074
https://doi.org/10.1016/j.neucom.2012.12.074