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1.
10th International Scientific Conference on Computer Science, COMSCI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2136145

ABSTRACT

In this paper we are presenting the results of creation and training of a stand-alone expert system aimed at detection and diagnosis of COVID infection, that is based on automatic readings of X-ray imaging X Ray, which determines whether the patient has COVID pneumonia. The system is realized with deep learning neural networks and is accelerated with GPU utilized, instead of CPU. © 2022 IEEE.

2.
2021 International Conference Automatics and Informatics, ICAI 2021 ; : 437-442, 2021.
Article in English | Scopus | ID: covidwho-1672701

ABSTRACT

This paper presents a system for COVID-19 detection with chest X-Ray scans as input data. The detection engine is implemented with Deep neural networks. The model of the generated Deep Learning Neural Network is trained with the use of chest X-Ray scans dataset as input data. The trained model was tested with new test image datasets and the results show that it provides a high enough recognition rate, providing that this methodology can be applied for quick and nonintrusive COVID-19 detection. © 2021 IEEE.

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