Residue number system-based solution for reducing the hardware cost of a convolutional neural network

Convolutional neural networks (CNNs) represent deep learning architectures that are currently used in a wide range of applications, including computer vision, speech recognition, time series analysis in finance, and many others. At the same time, CNNs are very demanding in terms of the hardware and...

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Detalles Bibliográficos
Главные авторы:	Chervyakov, N. I., Червяков, Н. И., Lyakhov, P. A., Ляхов, П. А., Deryabin, M. A., Дерябин, М. А., Nagornov, N. N., Нагорнов, Н. Н., Valueva, M. V., Валуева, М. В., Valuev, G. V., Валуев, Г. В.
Formato:	Статья
Idioma:	English
Publicado:	Elsevier B.V. 2020
Темы:	Convolutional neural networks FPGA Image recognition Quantization noise Residue number system (RNS)
Acceso en liña:	https://dspace.ncfu.ru/handle/20.500.12258/12151
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https://dspace.ncfu.ru/handle/20.500.12258/12151

Residue number system-based solution for reducing the hardware cost of a convolutional neural network

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