Zobrazeno 1 - 8
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pro vyhledávání: '"Nesma M. Rezk"'
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
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
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Information; Volume 13; Issue 4; Pages: 176
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
Publikováno v:
IPDPS Workshops
Convolution neural networks (CNN) are extensively used for deep learning applications such as image recognition and computer vision. The convolution module of these networks is highly compute-intensive. Having an efficient implementation of the convo
Publikováno v:
Progress in Artificial Intelligence ISBN: 9783319234847
EPIA
EPIA
Swarm robots are required to explore and search large areas. In order to cover largest possible area while keeping communications, robots try to maintain hexagonal formation while moving. Obstacle avoidance is an extremely important task for swarm ro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::630bbc163be6aa4731ad94640cd0424c
https://doi.org/10.1007/978-3-319-23485-4_49
https://doi.org/10.1007/978-3-319-23485-4_49
Publikováno v:
2014 9th International Conference on Computer Engineering & Systems (ICCES).
Obstacle avoidance is an extremely important task in swarm robotics as it saves robots from hitting objects and being damaged. A Genetic algorithm can be used to teach robots how to avoid obstacles in different environments. However the evaluation mo