Zobrazeno 1 - 10
of 1 480
pro vyhledávání: '"Bai Lei"'
Publikováno v:
Redai dili, Vol 44, Iss 9, Pp 1588-1601 (2024)
Global precipitation observations have been realized through the development of satellite remote-sensing technology. However, there is a lack of evaluation of remote-sensing precipitation products in complex tropical island terrains. This study used
Externí odkaz:
https://doaj.org/article/3a2c4129452146e1a9fdce4b598eb426
Publikováno v:
Asian Journal of Surgery, Vol 46, Iss 9, Pp 3941-3942 (2023)
Externí odkaz:
https://doaj.org/article/2886822c5cee4ad5a9248ccd1ef17732
Autor:
Yue, Xiaoyu, Wang, Zidong, Lu, Zeyu, Sun, Shuyang, Wei, Meng, Ouyang, Wanli, Bai, Lei, Zhou, Luping
Conventional class-guided diffusion models generally succeed in generating images with correct semantic content, but often struggle with texture details. This limitation stems from the usage of class priors, which only provide coarse and limited cond
Externí odkaz:
http://arxiv.org/abs/2410.08531
Autor:
Xu, Jingyi, Tu, Siwei, Yang, Weidong, Li, Shuhao, Liu, Keyi, Luo, Yeqi, Ma, Lipeng, Fei, Ben, Bai, Lei
Variation of Arctic sea ice has significant impacts on polar ecosystems, transporting routes, coastal communities, and global climate. Tracing the change of sea ice at a finer scale is paramount for both operational applications and scientific studie
Externí odkaz:
http://arxiv.org/abs/2410.09111
Autor:
Gong, Junchao, Tu, Siwei, Yang, Weidong, Fei, Ben, Chen, Kun, Zhang, Wenlong, Yang, Xiaokang, Ouyang, Wanli, Bai, Lei
Precipitation nowcasting plays a pivotal role in socioeconomic sectors, especially in severe convective weather warnings. Although notable progress has been achieved by approaches mining the spatiotemporal correlations with deep learning, these metho
Externí odkaz:
http://arxiv.org/abs/2410.05805
Numerical Weather Prediction (NWP) system is an infrastructure that exerts considerable impacts on modern society.Traditional NWP system, however, resolves it by solving complex partial differential equations with a huge computing cluster, resulting
Externí odkaz:
http://arxiv.org/abs/2409.16321
Much previous AI research has focused on developing monolithic models to maximize their intelligence and capability, with the primary goal of enhancing performance on specific tasks. In contrast, this paper explores an alternative approach: collabora
Externí odkaz:
http://arxiv.org/abs/2409.01392
Recent advancements in deep learning (DL) have led to the development of several Large Weather Models (LWMs) that rival state-of-the-art (SOTA) numerical weather prediction (NWP) systems. Up to now, these models still rely on traditional NWP-generate
Externí odkaz:
http://arxiv.org/abs/2408.11438
In an era of frequent extreme weather and global warming, obtaining precise, fine-grained near-surface weather forecasts is increasingly essential for human activities. Downscaling (DS), a crucial task in meteorological forecasting, enables the recon
Externí odkaz:
http://arxiv.org/abs/2408.10854
Existing EEW approaches often treat phase picking, location estimation, and magnitude estimation as separate tasks, lacking a unified framework. Additionally, most deep learning models in seismology rely on full three-component waveforms and are not
Externí odkaz:
http://arxiv.org/abs/2408.06629