Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Erik J. Linstead"'
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-12 (2022)
Abstract We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user accou
Externí odkaz:
https://doaj.org/article/f91f945aafb14cdf8db357b8ad8e7c82
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-10 (2020)
Abstract Background Transfer learning allows us to train deep architectures requiring a large number of learned parameters, even if the amount of available data is limited, by leveraging existing models previously trained for another task. In previou
Externí odkaz:
https://doaj.org/article/70ee77d769df445ab8d8103313e59019
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-10 (2019)
Abstract Background Despite the well-documented and numerous recent successes of deep learning, the application of standard deep architectures to many classification problems within empirical software engineering remains problematic due to the large
Externí odkaz:
https://doaj.org/article/9ca8bc62f6084b488e384376384fa6e4
Publikováno v:
Acta Astronautica. 200:262-269
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3b5110a3f0f92e881c2229a293e1fb2
https://doi.org/10.1016/j.actaastro.2022.08.017
https://doi.org/10.1016/j.actaastro.2022.08.017
Publikováno v:
Review Journal of Autism and Developmental Disorders.
Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcdb7cb88673cf74230ba79ef0cf12ac
https://doi.org/10.1007/s40489-021-00299-y
https://doi.org/10.1007/s40489-021-00299-y