Zobrazeno 1 - 6
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pro vyhledávání: '"Tomas Nordstrom"'
Publikováno v:
IEEE Access, Vol 8, Pp 57967-57996 (2020)
Recurrent Neural Networks (RNNs) are a class of machine learning algorithms used for applications with time-series and sequential data. Recently, there has been a strong interest in executing RNNs on embedded devices. However, difficulties have arise
Externí odkaz:
https://doaj.org/article/77be102290184011a7ea6b5356c0a369
Publikováno v:
Information, Vol 13, Iss 4, p 176 (2022)
Recurrent neural networks (RNNs) are neural networks (NN) designed for time-series applications. There is a growing interest in running RNNs to support these applications on edge devices. However, RNNs have large memory and computational demands that
Externí odkaz:
https://doaj.org/article/2eff7712d1e44a04ac0c7fd2b8165289
Autor:
Ramiro Sámano-Robles, Tomas Nordström, Kristina Kunert, Salvador Santonja-Climent, Mikko Himanka, Markus Liuska, Michael Karner, Eduardo Tovar
Publikováno v:
Technologies, Vol 9, Iss 4, p 99 (2021)
This paper presents the High-Level Architecture (HLA) of the European research project DEWI (Dependable Embedded Wireless Infrastructure). The objective of this HLA is to serve as a reference framework for the development of industrial Wireless Senso
Externí odkaz:
https://doaj.org/article/709507717782478b9b1ed550dee8f7cd
Publikováno v:
Computers, Vol 7, Iss 2, p 27 (2018)
The last ten years have seen performance and power requirements pushing computer architectures using only a single core towards so-called manycore systems with hundreds of cores on a single chip. To further increase performance and energy efficiency,
Externí odkaz:
https://doaj.org/article/d1e126f988644d73b9aa9c03a76dc4ed
Publikováno v:
Journal of Policy Analysis and Management. 4:284
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