Image recognition of COVID-19 using DarkCovidNet architecture based on convolutional neural network

Image recognition of COVID-19 using DarkCovidNet architecture based on convolutional neural network

Purpose The purpose of this study/paper To focus on finding COVID-19 with the help of DarkCovidNet architecture on patient images. Design/methodology/approach We used machine learning techniques with convolutional neural network. Findings Detecting COVID-19 symptoms from patient CT scan images. Orig...

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Veröffentlicht in:World journal of engineering 2022-02, Vol.19 (1), p.90-97
Hauptverfasser: Kumar, Pankaj, Bajpai, Bhavna, Gupta, Deepak Omprakash, Jain, Dinesh C., Vimal, S.
Format: Artikel
Sprache:eng
Schlagworte:
Artificial neural networks
Computed tomography
Coronaviruses
COVID-19
Datasets
Machine learning
Medical imaging
Medical research
Neural networks
Object recognition
X-rays
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Zusammenfassung:Purpose The purpose of this study/paper To focus on finding COVID-19 with the help of DarkCovidNet architecture on patient images. Design/methodology/approach We used machine learning techniques with convolutional neural network. Findings Detecting COVID-19 symptoms from patient CT scan images. Originality/value This paper contains a new architecture for detecting COVID-19 symptoms from patient computed tomography scan images.
ISSN:1708-5284
1708-5284
DOI:10.1108/WJE-12-2020-0655