DETECTION OF COVID 19 USING DEEP LEARNING APPROACH

Abstract

COVID-19 has been a major field for researchers to investigate it using deep learning techniques using Resnet, The prevalence rate of COVID-19 is rapidly raising everybody throughout the globe. Although no vaccines for this pandemic have been discovered yet, deep learning techniques proved themselves to be a powerful tool in the arsenal used by clinicians for the automatic diagnosis of COVID-19.A deep learning model is used to predict Covid-19 with high accuracy, The Reset introduces the concept of skip connection to facilitate the computation faster and results with less training error than other architectures, Reset combined batch normalization and individual residual units to solve the problem of vanishing gradients, degradation, low-quality image and provides a reasonable classification into infected of non-infected, with a average accuracy. Deep learning approach is used to provide more reliable diagnosis, specifically in resource limited areas and it also reduces the cost of diagnosis. In the proposed work, the image are passed through convolutional layer consists of residual units which is defined by Relu and Batch normalization. Finally, proceeded by fully connected layer to give the predicted output either covid-19 infected or uninfected images .This paper aims to overview the recently developed systems based on deep learning techniques using medicals imaging modalities like X- Ray.

Imprint

R. Breesha, D. Shofia Priyadharshini, K. Aishwarya, V. Vikrama Sundaran, A. Satihsh Agasteu, S. Sriman DETECTION OF COVID 19 USING DEEP LEARNING APPROACH. Cardiometry; No.26 February 2023; p.-; DOI: .; Available from: https://www.cardiometry.net/issues/no26-february-2023/detection-of-covid-19-using-deep-learning-approach