Zobrazeno 1 - 10
of 1 944
pro vyhledávání: '"Gui Mei"'
Publikováno v:
Photonics, Vol 11, Iss 5, p 461 (2024)
As a space camera works in orbit, the stress rebound caused by gravity inevitably results in the deformation of its optomechanical structure, and the relative position change between different optical components will affect the Line-Of-Sight pointing
Externí odkaz:
https://doaj.org/article/0b8f58cba0ae4090800cc848037eae8e
Autor:
Bo Chen, Xiao-Xin Zhang, Ling-Ping He, Ke-Fei Song, Shi-Jie Liu, Guang-Xing Ding, Jin-Ping Dun, Jia-Wei Li, Zhao-Hui Li, Quan-Feng Guo, Hai-Feng Wang, Xiao-Dong Wang, Yun-Qi Wang, Hong-Ji Zhang, Guang Zhang, Zhen-Wei Han, Shuang Dai, Pei-Jie Zhang, Liang Sun, Yang Liu, Peng Wang, Kun Wu, Chen Tao, Shi-Lei Mao, Gui Mei, Liang Yang, Li-Heng Chen, Chun-Yang Han, Bin Huang, Shuai Ren, Peng Zhou, Ze-Xi Wei, Xiao-Xue Zhang, Yue Zhang, Xin Zheng, Yang Wang, Ya Chen, Jing-Jiang Xie, Fei He, Qiao Song, Wei-Guo Zong, Xiu-Qing Hu, Peng Zhang, Jing-Song Wang, Zhong-Dong Yang
Publikováno v:
Light: Science & Applications, Vol 11, Iss 1, Pp 1-13 (2022)
Abstract The solar X-ray and Extreme Ultraviolet Imager (X-EUVI), developed by the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CIOMP), is the first space-based solar X-ray and Extreme ultraviolet (EUV) imag
Externí odkaz:
https://doaj.org/article/cb1d5eb9532842888646f4280852af63
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Gui, Mei-Jiang, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Li, Hao, Xiang, Tian-Yu, Hou, Zeng-Guang
Iodinated contrast agents are widely utilized in numerous interventional procedures, yet posing substantial health risks to patients. This paper presents CAS-GAN, a novel GAN framework that serves as a ``virtual contrast agent" to synthesize X-ray an
Externí odkaz:
http://arxiv.org/abs/2410.08490
Autor:
Yitong Li, Yu Chen, Wenli Xie, Xueni Li, Gui Mei, Jing Xu, Xiangpei Zhao, Hongli Teng, Guangzhong Yang
Publikováno v:
Frontiers in Chemistry, Vol 10 (2022)
Eight new phenolic compounds, named bercheminols A-H (1–8), and eleven known analogues were isolated from the stems and leaves of Berchemia lineata (L.) DC. Their structures including the absolute configurations were elucidated by extensive spectro
Externí odkaz:
https://doaj.org/article/0504583ed0fe4d8694866d6612d1fc91
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Yao, Bo-Xian, Hou, Zeng-Guang
Automatic vessel segmentation is paramount for developing next-generation interventional navigation systems. However, current approaches suffer from suboptimal segmentation performances due to significant challenges in intraoperative images (i.e., lo
Externí odkaz:
http://arxiv.org/abs/2406.19749
Autor:
Qin Yang, Qing Qing Tan, Chang Jun Lan, Bo Zhen Lv, Gui Mei Zhou, Wei Qi Zhong, Zhi Ming Gu, Yu Mei Mao, Xuan Liao
Publikováno v:
Frontiers in Physiology, Vol 12 (2021)
KCNQ5 is suggestively associated with myopia, but its specific role in the myopic process has not been studied further. The aim of this study was to investigate the expression of potassium channel gene KCNQ5 and the changes of K+ microenvironment wit
Externí odkaz:
https://doaj.org/article/3909b3eefd4945f889f2f1ba203246fc
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Liu, Xiu-Ling, Hou, Zeng-Guang
Medical image segmentation takes an important position in various clinical applications. Deep learning has emerged as the predominant solution for automated segmentation of volumetric medical images. 2.5D-based segmentation models bridge computationa
Externí odkaz:
http://arxiv.org/abs/2401.11856
Autor:
Liu, Xiao-Yin, Zhou, Xiao-Hu, Li, Guotao, Li, Hao, Gui, Mei-Jiang, Xiang, Tian-Yu, Huang, De-Xing, Hou, Zeng-Guang
Offline reinforcement learning (RL) faces a significant challenge of distribution shift. Model-free offline RL penalizes the Q value for out-of-distribution (OOD) data or constrains the policy closed to the behavior policy to tackle this problem, but
Externí odkaz:
http://arxiv.org/abs/2312.03991
Autor:
Li, Hao, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Feng, Zhen-Qiu, Liu, Xiao-Yin, Gui, Mei-Jiang, Xiang, Tian-Yu, Huang, De-Xing, Yao, Bo-Xian, Hou, Zeng-Guang
Offline reinforcement learning (RL) aims to optimize policy using collected data without online interactions. Model-based approaches are particularly appealing for addressing offline RL challenges due to their capability to mitigate the limitations o
Externí odkaz:
http://arxiv.org/abs/2310.17245
Autor:
Liu, Xiao-Yin, Zhou, Xiao-Hu, Gui, Mei-Jiang, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Li, Hao, Xiang, Tian-Yu, Huang, De-Xing, Hou, Zeng-Guang
Model-based reinforcement learning (RL), which learns environment model from offline dataset and generates more out-of-distribution model data, has become an effective approach to the problem of distribution shift in offline RL. Due to the gap betwee
Externí odkaz:
http://arxiv.org/abs/2309.08925