Detection of Covid-19 using Transfer Learning Technique
3rd IEEE International Conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022
; : 193-198, 2022.
Article
in English
| Scopus | ID: covidwho-2267477
ABSTRACT
The whole world is suffering from the wave of the novel coronavirus that causes the large-scale death of a population and is proclaimed a pandemic by WHO. As RT-PCR tests to detect Coronavirus are costly and time taking. So now these days, the purpose of the researcher is to detect these diseases with the help of Artificial Intelligence or Machine learning-based models using CT scan images and X-rays images. So the testing cost, time taken and the number of data required could be minimized. In this paper, transfer learning based on three fine-tuned models has been proposed for Covid detection. The performance of these proposed fine-tuned models has been also compared with other competing models to check the accuracy and other matrices. © 2022 IEEE.
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
3rd IEEE International Conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022
Year:
2022
Document Type:
Article
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