• Asish Kumar Dash
• Dr. S. V. G. Reddy

The effective screening of Covid-19 cases has been become extremely important to mitigate and stop the spread of the disease during the current period of Covid-19 pandemic worldwide. Radiology examination of using chest X-ray images, is one among the effective screening approaches for Covid-19 case detection. Deep learning is a powerful tool and framework for image analysis, and many studies have been conducted to detect Covid-19 cases using deep learning models trained on X-ray images. Although some of them claim to have good prediction results, their proposed deep learning models may suffer from high variance, overfitting and generalization errors due to noise and a limited number of datasets. As multilayer Convolution neural network (CNN) can overcome the short comings of deep learning by making predictions with more precision and processed inputs. In this proposed work the analysis of covid-19 case detection from chest x-ray images using VGG16, RESNET50, and customized CNN models is done and achieved maximum accuracy.

COVID- 19, Convolution neural networks (CNN), RESNET50, VGG16, Chest X- Ray images.

"ANALYSIS OF COVID-19 CASE DETECTION FROM CHEST X-RAY IMAGES USING VGG16, RESNET50 AND CUSTOMIZED CNN MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.b65-b72, May-2022, Available :http://www.jetir.org/papers/JETIR2205111.pdf

"ANALYSIS OF COVID-19 CASE DETECTION FROM CHEST X-RAY IMAGES USING VGG16, RESNET50 AND CUSTOMIZED CNN MODELS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppb65-b72, May-2022, Available at : http://www.jetir.org/papers/JETIR2205111.pdf