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检索条件"机构=Hubei Key Laboratory of Engineering Modeling and Science Computing"
534 条 记 录,以下是411-420 订阅
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Image saliency and co-saliency detection by low-rank multiscale fusion
Image saliency and co-saliency detection by low-rank multisc...
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作者: Huang, Rui Feng, Wei Sun, Jizhou Zou, Yaobin College of Computer Science and Technology Civil Aviation University of China Tianjin300300 China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang443003 China College of Intelligence and Computing School of Computer Science and Technology Tianjin University Tianjin300350 China Key Research Center for Surface Monitoring and Analysis of Cultural Relics State Administration of Cultural Heritage China
Saliency and co-saliency detection aim to distinguish conspicuous foreground objects from single and multiple images, thus are essential in many multimedia and vision applications. To achieve balanced efficiency and a... 详细信息
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Initial successive coefficients for certain classes of univalent functions involving the exponential function
arXiv
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arXiv 2020年
作者: SHI, LEI WANG, ZHI-GANG SU, REN-LI ARIF, MUHAMMAD School of Mathematics and Statistics Anyang Normal University Anyang Henan455002 China School of Mathematics and Computing Science Hunan First Normal University Changsha Hunan410205 China School of Mathematics and Statistics Changsha University of Science and Technology Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering Changsha Hunan410114 China Department of Mathematics Abdul Wali Khan University Mardan23200 Pakistan
Let S denote the family of all functions that are analytic and univalent in the unit disk D := {z : |z| MSC Codes Primary 30C45, Secondary 30C80 Copyright © 2020, The Authors. All rights reserved.
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Exploring Lorentz Invariance Violation from Ultrahigh-Energy γ Rays Observed by LHAASO
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Physical Review Letters 2022年 第5期128卷 051102-051102页
作者: Zhen Cao F. Aharonian Q. An Axikegu L. X. Bai Y. X. Bai Y. W. Bao D. Bastieri X. J. Bi Y. J. Bi H. Cai J. T. Cai Zhe Cao J. Chang J. F. Chang B. M. Chen E. S. Chen J. Chen Liang Chen Long Chen M. J. Chen M. L. Chen Q. H. Chen S. H. Chen S. Z. Chen T. L. Chen X. L. Chen Y. Chen N. Cheng Y. D. Cheng S. W. Cui X. H. Cui Y. D. Cui B. D’Ettorre Piazzoli B. Z. Dai H. L. Dai Z. G. Dai Danzengluobu D. della Volpe X. J. Dong K. K. Duan J. H. Fan Y. Z. Fan Z. X. Fan J. Fang K. Fang C. F. Feng L. Feng S. H. Feng Y. L. Feng B. Gao C. D. Gao L. Q. Gao Q. Gao W. Gao M. M. Ge L. S. Geng G. H. Gong Q. B. Gou M. H. Gu F. L. Guo J. G. Guo X. L. Guo Y. Q. Guo Y. Y. Guo Y. A. Han H. H. He H. N. He J. C. He S. L. He X. B. He Y. He M. Heller Y. K. Hor C. Hou X. Hou H. B. Hu S. Hu S. C. Hu X. J. Hu D. H. Huang Q. L. Huang W. H. Huang X. T. Huang X. Y. Huang Z. C. Huang F. Ji X. L. Ji H. Y. Jia K. Jiang Z. J. Jiang C. Jin T. Ke D. Kuleshov K. Levochkin B. B. Li Cheng Li Cong Li F. Li H. B. Li H. C. Li H. Y. Li Jian Li Jie Li K. Li W. L. Li X. R. Li Xin Li Y. Li Y. Z. Li Zhe Li Zhuo Li E. W. Liang Y. F. Liang S. J. Lin B. Liu C. Liu D. Liu H. Liu H. D. Liu J. Liu J. L. Liu J. S. Liu J. Y. Liu M. Y. Liu R. Y. Liu S. M. Liu W. Liu Y. Liu Y. N. Liu Z. X. Liu W. J. Long R. Lu H. K. Lv B. Q. Ma L. L. Ma X. H. Ma J. R. Mao A. Masood Z. Min W. Mitthumsiri T. Montaruli Y. C. Nan B. Y. Pang P. Pattarakijwanich Z. Y. Pei M. Y. Qi Y. Q. Qi B. Q. Qiao J. J. Qin D. Ruffolo V. Rulev A. Sáiz L. Shao O. Shchegolev X. D. Sheng J. R. Shi H. C. Song Yu. V. Stenkin V. Stepanov Y. Su Q. N. Sun X. N. Sun Z. B. Sun P. H. T. Tam Z. B. Tang W. W. Tian B. D. Wang C. Wang H. Wang H. G. Wang J. C. Wang J. S. Wang L. P. Wang L. Y. Wang R. N. Wang W. Wang X. G. Wang X. J. Wang X. Y. Wang Y. Wang Y. D. Wang Y. J. Wang Y. P. Wang Z. H. Wang Z. X. Wang Zhen Wang Zheng Wang D. M. Wei J. J. Wei Y. J. Wei T. Wen C. Y. Wu H. R. Wu S. Wu W. X. Wu X. F. Wu S. Q. Xi J. Xia J. J. Xia G. M. Xiang D. X. Xiao G. Xiao H. B. Xiao G. G. Xin Y. L. Xin Y. Xing D. L. Xu R. X. Xu L. Xue Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China University of Chinese Academy of Sciences 100049 Beijing China TIANFU Cosmic Ray Research Center Chengdu 610000 Sichuan China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany State Key Laboratory of Particle Detection and Electronics 100049 Beijing China University of Science and Technology of China 230026 Hefei Anhui China School of Physical Science and Technology and School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China College of Physics Sichuan University 610065 Chengdu Sichuan China School of Astronomy and Space Science Nanjing University 210023 Nanjing Jiangsu China Center for Astrophysics Guangzhou University 510006 Guangzhou Guangdong China School of Physics and Technology Wuhan University 430072 Wuhan Hubei China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences 210023 Nanjing Jiangsu China Hebei Normal University 050024 Shijiazhuang Hebei China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 200030 Shanghai China Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education 850000 Lhasa Tibet China National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China School of Physics and Astronomy and School of Physics (Guangzhou) Sun Yat-sen University 519000 Zhuhai Guangdong China Dipartimento di Fisica dell’Università di Napoli “Federico II ” Complesso Universitario di Monte Sant’Angelo via Cinthia 80126 Napoli Italy School of Physics and Astronomy Yunnan University 650091 Kunming Yunnan China Département de Physique Nucléaire et Corpusculaire Faculté de S
Recently, the LHAASO Collaboration published the detection of 12 ultrahigh-energy γ-ray sources above 100 TeV, with the highest energy photon reaching 1.4 PeV. The first detection of PeV γ rays from astrophysical so... 详细信息
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Analysis of L1-Galerkin FEMs for Time-Fractional Nonlinear Parabolic Problems
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Communications in Computational Physics 2018年 第6期24卷 86-103页
作者: Dongfang Li Hong-Lin Liao Weiwei Sun Jilu Wang Jiwei Zhang School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China Department of Mathematics City University of Hong KongKowloonHong Kong Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjing211106China Department of Scientific Computing Florida StateUniversityTallahasseeFL 32306USA Beijing Computational Science Research Center Beijing 100094China.
This paper is concerned with numerical solutions of time-fractional nonlinear parabolic problems by a class of L1-Galerkin finite element *** analysis of L1 methods for time-fractional nonlinear problems is limited ma... 详细信息
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General propagation lattice Boltzmann model for nonlinear advection-diffusion equations
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Physical Review E 2018年 第4期97卷 043310-043310页
作者: Xiuya Guo Baochang Shi Zhenhua Chai School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan 430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan 430074 China
In this paper, a general propagation lattice Boltzmann model is proposed for nonlinear advection-diffusion equations (NADEs), and the Chapman-Enskog analysis shows that the NADEs with variable coefficients can be reco... 详细信息
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Phase retrieval for sub-Gaussian measurements
arXiv
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arXiv 2019年
作者: Gao, Bing Liu, Haixia Wang, Yang School of Mathematical Sciences Nankai University Tianjin300071 China School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 Department of Mathematics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong
Generally, phase retrieval problem can be viewed as the reconstruction of a function/signal from only the magnitude of the linear measurements. These measurements can be, for example, the Fourier transform of the dens... 详细信息
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Shielding collaborative learning: Mitigating poisoning attacks through client-side detection
arXiv
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arXiv 2019年
作者: Zhao, Lingchen Hu, Shengshan Wang, Qian Jiang, Jianlin Shen, Chao Luo, Xiangyang School of Cyber Science and Engineering Wuhan University Wuhan Hubei430072 China School of Computer Science Wuhan University Wuhan Hubei430072 China School of Cyberspace Security Xian Jiaotong University Xi’an Shaanxi710049 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan450002 China
Collaborative learning allows multiple clients to train a joint model without sharing their data with each other. Each client performs training locally and then submits the model updates to a central server for aggreg... 详细信息
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A NEW PHYSICS-PRESERVING IMPES SCHEME FOR INCOMPRESSIBLE AND IMMISCIBLE TWO-PHASE FLOW IN HETEROGENEOUS POROUS MEDIA
arXiv
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arXiv 2019年
作者: Chen, Huangxin Shuyu, S.U.N. School of Mathematical Sciences Fujian Provincial Key Laboratory on Mathematical Modeling High Performance Scientific Computing Xiamen University Fujian361005 China Computational Transport Phenomena Laboratory Division of Physical Science Engineering King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia
In this work we consider a new efficient IMplicit Pressure Explicit Saturation (IMPES) scheme for the simulation of incompressible and immiscible two-phase flow in heterogeneous porous media with capillary pressure. C... 详细信息
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Ergodic optimization theory for a class of typical maps
arXiv
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arXiv 2019年
作者: Huang, Wen Lian, Zeng Ma, Xiao Xu, Leiye Zhang, Yiwei Wu Wen-Tsun Key Laboratory of Mathematics USTC Chinese Academy of Sciences Department of Mathematics University of Science and Technology of China Hefei Anhui China College of Mathematical Sciences Sichuan University Chengdu Sichuan610016 China School of Mathematics and Statistics Center for Mathematical Sciences Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Sciences and Technology Wuhan430074 China
In this article, we consider the weighted ergodic optimization problem of a class of dynamical systems T: X → X where X is a compact metric space and T is Lipschitz continuous. We show that once T: X → X satisfies b... 详细信息
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Designing and Training of A Dual CNN for Image Denoising
arXiv
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arXiv 2020年
作者: Zuo, Wangmeng Zhang, David Lin, Chia-Wen Xu, Yong Tian, Chunwei Du, Bo Bio-Computing Research Center Harbin Institute of Technology Shenzhen China Shenzhen Key Laboratory of Visual Object Detection and Recognition ShenzhenGuangdong518055 China Peng Cheng Laboratory Shenzhen518055 China School of Computer Science and Technology Harbin Institute of Technology 150001 HarbinHeilongjiang China Peng Cheng Laboratory Shenzhen518055 China School of Computer Science Wuhan University 430072 WuhanHubei China Department of Electrical Engineering Institute of Communications Engineering National Tsing Hua University Hsinchu Taiwan 518172 ShenzhenGuangdong China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China
Deep convolutional neural networks (CNNs) for image denoising have recently attracted increasing research interest. However, plain networks cannot recover fine details for a complex task, such as real noisy images. In... 详细信息
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