COVID-19 identification in ct images based on deep learning models: a comparative approach

People's lives could be in danger if a contagious disease spreads quickly, Corona-2019 virus (COVID-19) is one. The coronavirus epidemic rapidly spread over the world. Corona has had major impact on health of populations and healthcare systems all RT-PCR (RT-Reverse transcription, PCR-polymerase chain reaction) testing can benefit from use computed tomography images. Most available methods large training data, detection accuracy needs to improved due inadequate border segment symptom descriptions. This study proposes robust effective way for identifying normal COVID-19 patients using small data. Deep learning quickly creates accurate models. Data augmentation increases dataset reduce fitting improve model generalisation. Using data augmentation, we evaluated Xception VGG-19. showed that deep detect COVID-19.