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Fast Convolution units for Convolutional Neural Network

    Authors

    • M.V.Nageswara Rao 1
    • A. Sudhakar 2

    1 Professor, Department of ECE, GMR Institute of Technology, Rajam, India

    2 Associate Professor, Department of ECE, GMR Institute of Technology, Rajam, India.

,

Document Type : Research Article

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Abstract

Convolution neural network is basically an algorithm which is used to train a model to perform a specific task, which is inspired by the working of the human brain. Nowadays, its being extensively used in various applications. Its implementation over the FPGA board not only reduces the development time, but also increases the programmability. In this paper, Fast Convolution unit is described, which are based on parallel fast finite impulse response algorithm (FFA). This paper also includes the derivation of the algorithm.

Keywords

  • Convolution neural networks
  • Rectified Linear Unit
  • Parallel fast finite impulse response algorithm
  • Polling Layers
  • Fully connected layers
  • DCCN
  • FPGA
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    • Article View: 199
    • PDF Download: 348
European Journal of Molecular & Clinical Medicine
Volume 7, Issue 4
November 2020
Page 2872-2877
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  • Article View: 199
  • PDF Download: 348

APA

Rao, M., & Sudhakar, A. (2020). Fast Convolution units for Convolutional Neural Network. European Journal of Molecular & Clinical Medicine, 7(4), 2872-2877.

MLA

M.V.Nageswara Rao; A. Sudhakar. "Fast Convolution units for Convolutional Neural Network". European Journal of Molecular & Clinical Medicine, 7, 4, 2020, 2872-2877.

HARVARD

Rao, M., Sudhakar, A. (2020). 'Fast Convolution units for Convolutional Neural Network', European Journal of Molecular & Clinical Medicine, 7(4), pp. 2872-2877.

VANCOUVER

Rao, M., Sudhakar, A. Fast Convolution units for Convolutional Neural Network. European Journal of Molecular & Clinical Medicine, 2020; 7(4): 2872-2877.

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