Self- Supervised Learning Based Covid-19 Detection from Chest Radiography Images Using Deep CNN

Corona Disease (COVID19) is an infectious disease that is rapidly producing respiratory contaminations and demanding medical attention on a global scale. It has had a profound effect on people lives, society, and the global economy. Due of the severe limitations of RT-PCR (switch record polymerase chain reaction)-based methods for COVID19 diagnosis, various healthcare-based imaging approaches have lately been used. In this paper, we generated a freely available dataset with a extensive number of CT scans which were positive for COVID-19. Next utilizing a least amount of training X-ray images, we build sample-efficientdeep learning approaches that really. Extensive testing demonstrated that the suggested Self-Trans method achieves aa lot of cutting-edge benchmarks. Our proposed approach detects COVID-19 instances with a reliability rate of 98.7% and COVID-19 infection could be identified with high precision by CT imaging.