ABSTRACT
The world is still experiencing the devastation caused by the covid-19 virus. It is vital not only to promote the vaccine and have people vaccinated as soon as possible, but it is also important to test more individuals and isolate those who are sick from the general population and stop the disease’s spread. While the nasal swab test model is now used over the world to identify covid patients, radiography evaluation provides an alternative and more efficient method. In this suggested system, a covid-19 detection model is used to detect the virus more quickly and inexpensively using the proposed Customized Deep Convolutional Neural Network (CDCNN) approach and chest x-rays. The CDCNN method utilizes both positive and negative covid affected patient chest x-rays to train the model and help with early prediction of covid-19. The output accuracy of the proposed model is 97.93 percent when using openly accessible chest X-ray images.
