A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19

This paper designs and develops a computational intelligence-based framework using convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19 cases. The framework utilizes a multi-access edge computing technology such that end-user can access available resources as well the CNN...

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Vydané v:	The Journal of supercomputing Ročník 78; číslo 7; s. 10250 - 10274
Hlavní autori:	Hassan, Md Rafiul, Ismail, Walaa N., Chowdhury, Ahmad, Hossain, Sharara, Huda, Shamsul, Hassan, Mohammad Mehedi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.05.2022 Springer Nature B.V
Predmet:	5G mobile communication Artificial intelligence Artificial neural networks Automation Cell phones Cloud computing Compilers Computer Science Coronaviruses COVID-19 Disease transmission Edge computing Genetic algorithms Image classification Image quality Interpreters Mobile computing Processor Architectures Programming Languages Task complexity COVID-19 CNN Classification Genetic Algorithm Multi-access edge
ISSN:	0920-8542, 1573-0484
On-line prístup:	Získať plný text
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