Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Ruoyan ZHAO"'
Publikováno v:
Dianxin kexue, Vol 37, Pp 57-66 (2021)
The dynamic migration technology of virtual machine provides a strong support for the resource scheduling of virtualization system.As one of the two core algorithms of virtual machine dynamic migration, Post-Copy algorithm has been a hot issue for sc
Externí odkaz:
https://doaj.org/article/ff36583d9b8e439d98b031e2ff9e8aa9
Publikováno v:
Dianxin kexue, Vol 36, Pp 31-38 (2020)
The unbalanced development status of network security was introduced.The main hazards and the mechanism model of penetration testing were described,and the inherent shortcomings of many existing traditional defense methods were analyzed.However,new m
Externí odkaz:
https://doaj.org/article/bc8e1509438d46059d573b5b772a3a1f
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2020 (2020)
Deep convolutional neural networks have been successfully applied to face detection recently. Despite making remarkable progress, most of the existing detection methods only localize each face using a bounding box, which cannot segment each face from
Externí odkaz:
https://doaj.org/article/c39896de9ddc44fc97df1f3fbb43e543
Publikováno v:
Applied Soft Computing. 142:110300
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::708650825671c4311e1d6d11154cfab6
https://doi.org/10.1016/j.asoc.2023.110300
https://doi.org/10.1016/j.asoc.2023.110300
Publikováno v:
2022 IEEE 38th International Conference on Data Engineering (ICDE).
Federated Recommendation (FR) has received considerable popularity and attention in the past few years. In FR, for each user, its feature vector and interaction data are kept locally on its own client thus are private to others. Without the access to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2777af45424a37179989ac0e9dda21df
https://doi.org/10.1109/icde53745.2022.00243
https://doi.org/10.1109/icde53745.2022.00243
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2020 (2020)
Deep convolutional neural networks have been successfully applied to face detection recently. Despite making remarkable progress, most of the existing detection methods only localize each face using a bounding box, which cannot segment each face from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b099df27db018940ab360635a4c01ef
https://doi.org/10.1155/2020/9242917
https://doi.org/10.1155/2020/9242917
Publikováno v:
Expert Systems with Applications. 209:118221
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::276f57471b434f4a1512d7f5d7170637
https://doi.org/10.1016/j.eswa.2022.118221
https://doi.org/10.1016/j.eswa.2022.118221
Publikováno v:
Annals of Operations Research.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f966df03b1547bc02be24b6eb490e100
https://doi.org/10.1007/s10479-021-04358-9
https://doi.org/10.1007/s10479-021-04358-9
Autor:
Yonghua Li, Ruoyan Zhao, Jian Xu, Shenggang Wu, Jianping Liu, Mengfan Pan, Lei Lei, Lijun Zhang, Yi Lu
Publikováno v:
2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS).
This paper presents an analytical discretization approach for continuous-time systems. By using the matrix multiplying expression of the state transition matrix and the matrix quadratic form theory, the general discretized model of the system state e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c103721a2b4dedc4c43bcc6d3efbccf9
https://doi.org/10.1109/ddcls49620.2020.9275088
https://doi.org/10.1109/ddcls49620.2020.9275088
Publikováno v:
Journal of Physics: Conference Series. 1176:032048
There are more than 18,000 butterflies in the world. Butterflies are essential cultural insects and have great significance in the field of insect research. However, due to its high similarity, various type, and the characteristics of the distinction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::caa5db57dfb8f06379cad8b9fd3bc913
https://doi.org/10.1088/1742-6596/1176/3/032048
https://doi.org/10.1088/1742-6596/1176/3/032048