Zobrazeno 1 - 10
of 624
pro vyhledávání: '"Wang Linwei"'
Autor:
Bajracharya, Pradeep, Toledo-Marín, Javier Quetzalcóatl, Fox, Geoffrey, Jha, Shantenu, Wang, Linwei
High-performance scientific simulations, important for comprehension of complex systems, encounter computational challenges especially when exploring extensive parameter spaces. There has been an increasing interest in developing deep neural networks
Externí odkaz:
http://arxiv.org/abs/2407.07674
Large Vision-Language Models (LVLMs) have shown significant potential in assisting medical diagnosis by leveraging extensive biomedical datasets. However, the advancement of medical image understanding and reasoning critically depends on building hig
Externí odkaz:
http://arxiv.org/abs/2406.19973
Autor:
Wang Linwei
Publikováno v:
Zhishi guanli luntan, Vol 5, Iss 5, Pp 271-282 (2020)
[Purpose/significance] The purpose of this paper is to find a new breakthrough in the prevention and control of public opinion by quantifying the vocabulary frequency of hot netizens' microblog and summarizing their concerns in public emergencies.[Me
Externí odkaz:
https://doaj.org/article/7b8481e82abe422489ca91d6a6795304
Publikováno v:
南方能源建设, Vol 7, Iss 2, Pp 148-156 (2020)
[Introduction] The increasing traffic and the increasingly tight construction cause the roads to be widened and rebuilt. In order to further study the stability of the embankment, the change of the mechanical characteristics of the pile under the ori
Externí odkaz:
https://doaj.org/article/9ac316c68d4443f3a6e161dfcc8ce4c2
Autor:
Jiang, Xiajun, Vadhavkar, Sumeet, Ye, Yubo, Toloubidokhti, Maryam, Missel, Ryan, Wang, Linwei
Personalized virtual heart models have demonstrated increasing potential for clinical use, although the estimation of their parameters given patient-specific data remain a challenge. Traditional physics-based modeling approaches are computationally c
Externí odkaz:
http://arxiv.org/abs/2403.15433
In dynamic positron emission tomography (PET) reconstruction, the importance of leveraging the temporal dependence of the data has been well appreciated. Current deep-learning solutions can be categorized in two groups in the way the temporal dynamic
Externí odkaz:
http://arxiv.org/abs/2403.07364
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series. This presents a significant challenge of identifiability: many abstract latent representations may reconstruct observations, yet do t
Externí odkaz:
http://arxiv.org/abs/2403.08194
The surgical environment imposes unique challenges to the intraoperative registration of organ shapes to their preoperatively-imaged geometry. Biomechanical model-based registration remains popular, while deep learning solutions remain limited due to
Externí odkaz:
http://arxiv.org/abs/2403.06901