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

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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Autori principali: 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.
Natura: Статья
Lingua:English
Pubblicazione: Elsevier B.V. 2020
Soggetti:
Convolutional neural networks
FPGA
Image recognition
Quantization noise
Residue number system (RNS)
Accesso online:https://dspace.ncfu.ru/handle/20.500.12258/12151
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https://dspace.ncfu.ru/handle/20.500.12258/12151

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