Zobrazeno 1 - 10
of 1 496
pro vyhledávání: '"Daniel Zeng"'
Autor:
Yuejiao Wang, Dajun Daniel Zeng, Qingpeng Zhang, Pengfei Zhao, Xiaoli Wang, Quanyi Wang, Yin Luo, Zhidong Cao
Publikováno v:
Fundamental Research, Vol 2, Iss 2, Pp 311-320 (2022)
Introduction: Multivariate time series prediction of infectious diseases is significant to public health, and the deep learning method has attracted increasing attention in this research field. Material and methods: An adaptively temporal graph convo
Externí odkaz:
https://doaj.org/article/5dacc7ef1dd349d7991128feadd59a96
Publikováno v:
Journal of Safety Science and Resilience, Vol 2, Iss 3, Pp 146-156 (2021)
The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science. Tremendous unstructured COVID-19 publications make it challenging for policymakers to obtain relevant evidence. Know
Externí odkaz:
https://doaj.org/article/781f8e88c2404c23a2134496af9346ac
Publikováno v:
IEEE Access, Vol 7, Pp 19954-19964 (2019)
The actionable behavioral rules suggest specific actions that may influence certain behavior in the stakeholders' best interest. In mining such rules, it was assumed previously that all attributes are categorical while the numerical attributes have b
Externí odkaz:
https://doaj.org/article/2e4d26c4a3214455b5fa7a1ed41aa20b
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-12
Publikováno v:
Neurocomputing. 510:59-68
Publikováno v:
IEEE Intelligent Systems. 37:45-53
Autor:
Zhidong Cao, Yuejiao Wang, Qingpeng Zhang, Yin Luo, Pengfei Zhao, Quanyi Wang, Dajun Daniel Zeng, Xiaoli Wang
Publikováno v:
Fundamental Research
Introduction Multivariate time series prediction of infectious diseases is significant to public health, and the deep learning method has attracted increasing attention in this research field. Material and methods An adaptively temporal graph convolu
Publikováno v:
IEEE Intelligent Systems. 37:71-78
Autor:
Buckeridge, David
Publikováno v:
In Journal of Biomedical Informatics April 2012 45(2):388-389
Publikováno v:
IEEE Intelligent Systems. 36:3-12
Multimodal data analysis has drawn increasing attention with the explosive growth of multimedia data. Although traditional unimodal data analysis tasks have accumulated abundant labeled datasets, there are few labeled multimodal datasets due to the d