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pro vyhledávání: '"Zhang Xiaoxuan"'
Deep learning (DL)-based sea\textendash land clutter classification for sky-wave over-the-horizon-radar (OTHR) has become a novel research topic. In engineering applications, real-time predictions of sea\textendash land clutter with existing distribu
Externí odkaz:
http://arxiv.org/abs/2402.06315
Three-dimensional digital subtraction angiography (3D-DSA) is a widely adopted technique for clinical evaluation of contrast-enhanced vasculatures. The distribution of a contrast agent such as iodine is often estimated via temporal subtraction. Advan
Externí odkaz:
http://arxiv.org/abs/2310.10694
Autor:
Zhang, Xiaoxuan, Gupta, Tryaksh, Wang, Zhenlin, Trewartha, Amalie, Anapolsky, Abraham, Garikipati, Krishna
In this work, we present a computational framework for coupled electro-chemo-(nonlinear) mechanics at the particle scale for solid-state batteries. The framework accounts for interfacial fracture between the active particles and solid electrolyte due
Externí odkaz:
http://arxiv.org/abs/2309.13463
Deep convolutional neural network has made great achievements in sea-land clutter classification for over-the-horizon-radar (OTHR). The premise is that a large number of labeled training samples must be provided for a sea-land clutter classifier. In
Externí odkaz:
http://arxiv.org/abs/2305.04021
In the sea-land clutter classification of sky-wave over-the-horizon-radar (OTHR), the imbalanced and scarce data leads to a poor performance of the deep learning-based classification model. To solve this problem, this paper proposes an improved auxil
Externí odkaz:
http://arxiv.org/abs/2301.00947
Autor:
Zhang, Xiaoxuan, Garikipati, Krishna
Traditional, numerical discretization-based solvers of partial differential equations (PDEs) are fundamentally agnostic to domains, boundary conditions and coefficients. In contrast, machine learnt solvers have a limited generalizability across these
Externí odkaz:
http://arxiv.org/abs/2301.13165
Autor:
Zhang, Xiaoxuan1 (AUTHOR) 230320261472@stu.haust.edu.cn, Liu, Jin1 (AUTHOR) 220320261813@stu.haust.edu.cn, Zhang, Chenglin1 (AUTHOR) 220320261787@stu.haust.edu.cn, Zhao, Yueyun1,2 (AUTHOR) 230320261501@stu.haust.edu.cn, Du, Xinwu1,2,3 (AUTHOR) du_xinwu@sina.com
Publikováno v:
Agronomy. Sep2024, Vol. 14 Issue 9, p2131. 17p.
Autor:
Yue, Baiqiao1,2,3 (AUTHOR) 211327018@fzu.edu.cn, Zhang, Xiaoxuan1,2,3 (AUTHOR), Lu, Kaiqing2,3,4 (AUTHOR), Ma, Haibao2,3 (AUTHOR), Chen, Chen5 (AUTHOR) angela_chen@nudt.edu.cn, Lin, Yue2,3,6 (AUTHOR) angela_chen@nudt.edu.cn
Publikováno v:
Polymers (20734360). Sep2024, Vol. 16 Issue 17, p2467. 11p.
Autor:
Denberg, David, Zhang, Xiaoxuan, Stern, Tomer, Wieschaus, Eric, Garikipati, Krishna, Shvartsman, Stanislav Y.
Publikováno v:
In Biophysical Journal 19 November 2024 123(22):3911-3922
Autor:
Peng, Yuan, Zhang, Yuxin, Wang, Wei, Liu, Biying, Zhang, Zuojing, Gong, Zhihao, Zhang, Xiaoxuan, Xia, Yuefeng, You, Xingji, Wu, Jingxiang
Publikováno v:
In European Journal of Pharmacology 15 September 2024 979