Zobrazeno 1 - 10
of 2 516
pro vyhledávání: '"Wang, ZhiWen"'
Autor:
He, Zhicheng, Chen, Zhifu, Liu, Guilin, Wang, Tinggui, Ho, Luis C., Wang, Junxian, Bian, Weihao, Cai, Zheng, Mou, Guobin, Gu, Qiusheng, Wang, Zhiwen
Publikováno v:
Science China Physics, Mechanics & Astronomy, 67, 129512, (2024)
Galactic-wide outflows driven by active galactic nuclei (AGNs) is a routinely invoked feedback mechanism in galaxy evolution models. Hitherto, the interplay among the interstellar gas on galactic scales, the propagation of AGN outflows and the fundam
Externí odkaz:
http://arxiv.org/abs/2408.04458
In the fast-evolving field of medical image analysis, Deep Learning (DL)-based methods have achieved tremendous success. However, these methods require plaintext data for training and inference stages, raising privacy concerns, especially in the sens
Externí odkaz:
http://arxiv.org/abs/2403.16473
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 9, p e19468 (2020)
BackgroundCaring for people with dementia is perceived as one of the most stressful and difficult forms of caring. Family caregivers always experience high levels of psychological burden and physical strain, so effective and practical support is esse
Externí odkaz:
https://doaj.org/article/9ac88aab40fc4dd6bcb21145497cb29f
Autor:
Wu, Yuhui, Wang, Guoqing, Wang, Zhiwen, Yang, Yang, Li, Tianyu, Zhang, Malu, Li, Chongyi, Shen, Heng Tao
Low-light image enhancement (LLIE) has achieved promising performance by employing conditional diffusion models. Despite the success of some conditional methods, previous methods may neglect the importance of a sufficient formulation of task-specific
Externí odkaz:
http://arxiv.org/abs/2312.12826
Deep learning (DL) has made significant advancements in tomographic imaging, particularly in low-dose computed tomography (LDCT) denoising. A recent trend involves servers training powerful models with large amounts of self-collected private data and
Externí odkaz:
http://arxiv.org/abs/2310.09101
Machine learning has been successfully applied to various fields of scientific computing in recent years. In this work, we propose a sparse radial basis function neural network method to solve elliptic partial differential equations (PDEs) with multi
Externí odkaz:
http://arxiv.org/abs/2309.03107
Recently, uncertainty-aware methods have attracted increasing attention in semi-supervised medical image segmentation. However, current methods usually suffer from the drawback that it is difficult to balance the computational cost, estimation accura
Externí odkaz:
http://arxiv.org/abs/2307.08988
For a graph $G$, let $\mathcal{S}(G)$ be the set consisting of Hermitian matrices whose graph is $G$. Denoted by $m_B(G,\lambda)$ the multiplicity of an eigenvalue $\lambda$ of $B(G)\in \mathcal{S}(G)$, we show that $m_B(G,\lambda)\le 2\theta(G)+p(G)
Externí odkaz:
http://arxiv.org/abs/2306.13882
Publikováno v:
Cailiao Baohu, Vol 57, Iss 8, Pp 130-146 (2024)
Although the development of laser surface strengthening and surface micro-nano structure manufacturing technologies in China began relatively late， it has progressed rapidly in recent years.Significant advancements have been made in areas such as t
Externí odkaz:
https://doaj.org/article/c7e07ca861b444ad88e7c93f379cd6b1