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Implementation of Neural Networks in FPGA

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Field Value
 
Title Implementation of Neural Networks in FPGA
 
Creator B, Jayanthi
Kumar, Lakshmi Sutha
 
Subject Artificial intelligence
Artificial neural network
Convolutional neural network
 
Description 57-63
Artificial Intelligence (AI) refers to the recreation of human intelligence in machines that have been designed to think
like humans and mimic their actions. AI has been used in many fields such as image processing, health care, education, and
marketing. Machine Learning (ML) has been the sub-division of AI, and deep learning has been the subdivision of ML.
Artificial Neural Network has been the most predominantly used deep learning technique. While implementing the ANN
technique, knowing whether the implementation could have been done in hardware or software becomes necessary, which is
essential to achieve the expected performance. This paper gives a survey on the available methods in which the ANN
architecture has been implemented to achieve efficient output with minimal resources. It is vital to study and analyze various
strategies for implementation and their functionality. This paper has also explained the advantages and disadvantages of
different implementation techniques that allow selecting the most appropriate hardware and respective methodology for
optimizing the hardware.
 
Date 2021-12-28T09:47:13Z
2021-12-28T09:47:13Z
2021-06
 
Type Article
 
Identifier 0975-105X (Online); 0367-8393 (Print)
http://nopr.niscair.res.in/handle/123456789/58761
 
Language en
 
Publisher NIScPR-CSIR, India
 
Source IJRSP Vol.50(2) [June 2021]