Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Kashiparekh, Kathan"'
Training deep neural networks often requires careful hyper-parameter tuning and significant computational resources. In this paper, we propose ConvTimeNet (CTN): an off-the-shelf deep convolutional neural network (CNN) trained on diverse univariate t
Externí odkaz:
http://arxiv.org/abs/1904.12546
Autor:
Ernala SK; Georgia Institute of Technology, USA., Kashiparekh KH; Georgia Institute of Technology, USA., Bolous A; Georgia Institute of Technology, USA., Ali A; Zucker Hillside Hospital, Psychiatry Research, USA., John M Kane; Zucker Hillside Hospital, Psychiatry Research, USA., Birnbaum ML; Zucker Hillside Hospital, Psychiatry Research, USA., DE Choudhury M; Georgia Institute of Technology, USA.
Publikováno v:
Proceedings of the ACM on human-computer interaction [Proc ACM Hum Comput Interact] 2021 Apr; Vol. 5 (CSCW1). Date of Electronic Publication: 2021 Apr 22.
