Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Shicheng Wen"'
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4432 (2023)
Deep learning has gained widespread interest in the task of building semantic segmentation modelling using remote sensing images; however, neural network models require a large number of training samples to achieve better classification performance,
Externí odkaz:
https://doaj.org/article/a53d2fa05bee4a3dab2a2ed550dca768
Publikováno v:
Computers & Geosciences. 83:65-71
Conditional nonlinear optimal perturbation (CNOP) 1 has been widely applied to predictability and sensitivity studies of nonlinear models in meteorology and oceanography. The popular solution of CNOP is based on adjoint models, which is also treated
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4a055054b8796f9a9a376f915fa4ca3
https://doi.org/10.1016/j.cageo.2015.06.016
https://doi.org/10.1016/j.cageo.2015.06.016
Publikováno v:
CEC
Conditional nonlinear optimal perturbation (CNOP) is an initial perturbation evolving into the largest nonlinear evolution at the prediction time. It has become a useful tool in meteorology and oceanography. The common method for solving the CNOP is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e639525af5e30d89237099d49790f06
https://doi.org/10.1109/cec.2015.7257067
https://doi.org/10.1109/cec.2015.7257067
Publikováno v:
Intelligent Computing Theories and Methodologies ISBN: 9783319221793
ICIC (1)
ICIC (1)
Conditional nonlinear optimal perturbation (CNOP) has been widely used in the predictability and sensitivity studies of the weather or climate models. The popular solution to the CNOP is the adjoint-based method. However, many numerical models have n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b37fcd9c1001ecf2ac9f15b39fd2863f
https://doi.org/10.1007/978-3-319-22180-9_59
https://doi.org/10.1007/978-3-319-22180-9_59
Publikováno v:
Intelligent Computing Theory ISBN: 9783319093321
ICIC (1)
ICIC (1)
Conditional nonlinear optimal perturbation has been widely used in predictability and sensitivity studies of nonlinear numerical models. The main solution for CNOP is the adjoint-based method. However, many modern numerical models have no adjoint mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::752614cba60fbdd6cc978ba7df5c9749
https://doi.org/10.1007/978-3-319-09333-8_14
https://doi.org/10.1007/978-3-319-09333-8_14
Publikováno v:
Algorithms and Architectures for Parallel Processing ISBN: 9783319111964
ICA3PP (1)
ICA3PP (1)
Conditional nonlinear optimal perturbation (CNOP) is an initial perturbation evolving into the largest nonlinear evolution at the prediction time. It has played an important role in predictability and sensitivity studies of nonlinear numerical models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c85c0732dd8f3781ba9f25000dd0ad4
https://doi.org/10.1007/978-3-319-11197-1_51
https://doi.org/10.1007/978-3-319-11197-1_51
Publikováno v:
HPCC/EUC
Adjoint model is one of the key technologies of numerical weather forecasting. In adjoint model, the observed information can be inputted into the model continually to improve the quality of the initial data and thus to improve the quality of forecas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afbeafaf478e8b351a5583683dea7759
https://doi.org/10.1109/hpcc.and.euc.2013.19
https://doi.org/10.1109/hpcc.and.euc.2013.19
Autor:
Shicheng Wen, Hongyu Li
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9783642255526
Eigen-decomposition plays a critical role in spectral segmentation. However it is often of low efficiency due to the bottleneck of computation. To solve such bottleneck problem, this paper proposes a dynamic image segmentation method with the increme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb1667dccf3730a8aa43c0a28ccec81a
https://doi.org/10.1007/978-3-642-25553-3_33
https://doi.org/10.1007/978-3-642-25553-3_33
Publikováno v:
International Journal of Computational Science and Engineering. 11:349
Conditional nonlinear optimal perturbation CNOP has been widely applied to predictability and sensitivity studies of nonlinear models. The popular methods of solving CNOP can be divided into two categories: adjoint-based and ensemble-based. Although
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c85dadf536872e576eb558a7ae17cd92
https://doi.org/10.1504/ijcse.2015.073494
https://doi.org/10.1504/ijcse.2015.073494
Autor:
Wang, Yanjun1,2 (AUTHOR) wangyanjun@hnust.edu.cn, Lin, Yunhao1,2 (AUTHOR), Huang, Huiqing3,4 (AUTHOR), Wang, Shuhan1,2 (AUTHOR), Wen, Shicheng5,6 (AUTHOR), Cai, Hengfan1,2 (AUTHOR)
Publikováno v:
Remote Sensing. Sep2023, Vol. 15 Issue 18, p4432. 24p.