Artificial Intelligence Exposure of COVID-19 from X - Ray Images using Deep Learning Techniques

AUTHOR(S)

Mr.K. Nagaraju, Dr. Tryambak A. Hiwarkar

DOI: https://doi.org/10.46647/ijetms.2023.v07i05.048

ABSTRACT
The new coronavirus (COVID19) is contagious the epidemic was declared a pandemic in March 2020.Therefore, easy and quick infection, the corona virus has caused thousands of deaths worldwide. Hence the development of new systems Accurate and rapid detection of COVID19 is becoming crucial. x-ray imaging is used by radiologists to diagnose the coronavirus. However, this process requires a lot of time. Therefore, AI systems can help reduce the pressure healthcare systems. In this article, we propose CoviNet a Deep Learning Network to automatically detect the presence of COVID19 on chest X-rays. The proposed architecture is based on of Adaptive Median filter, Histogram Smoothing and a Convolutional Neural Network(CNN). It is trained end to end a publicly available dataset. Our model achieved accuracy 98.75% in binary classification and 95.77% in multiple classification Because early diagnosis can limit the spread of the disease virus, this framework can be used to help radiologists first diagnosis of COVID19.

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How to Cite This Article:
Mr.K. Nagaraju, Dr. Tryambak A. Hiwarkar . Artificial Intelligence Exposure of COVID-19 from X - Ray Images using Deep Learning Techniques . ijetms;7(5):400-407. DOI: 10.46647/ijetms.2023.v07i05.048