@article{Sushma Dewangan_2021, title={CNN Model To Detect Covid - 19 From Chest X-Ray images}, url={http://www.thedesignengineering.com/index.php/DE/article/view/4340}, abstractNote={<p>The new COVID-19 is caused by the virus SARS-CoV-2. The most likely ecological reservoirs for SARS-CoV-2 are bats,but it is believed that the virus jumped the species barrier to humans from another intermediate animal host.COVID-19 is a respiratory disease, one that especially reaches into your respiratory tract, which includes your lungs.COVID-19 can cause a range of breathing problems, from mild to critical. Older adults and people who have other health conditions like heart disease, cancer, and diabetes may have more serious symptoms.Since the early recognition plays a major role in the diagnosis of NCOV-19 and can enhance long-term endurance rates. Medical imaging is an extremely significant method for early recognition and diagnosis of NCOV-19. But, manual analysis of a huge number of medical images can be time-consuming and tedious and effortlessly causes mistakes and human bias. So, X-ray images and computer tomography (CT) were used to support doctors in inferring medical images to advance their effectiveness[6].In this paper we have proposed a Deep Convolutional Neural Network-based solution which can detect the COVID-19 +ve patients using chest X-Ray images.The proposed approach gave a classification accuracy of 97.31% which is higher than the state-of-the-art CNN models as well the compared benchmark algorithm.</p&gt;}, journal={Design Engineering}, author={Sushma Dewangan, Yogesh Panjwani, Padmavati Shrivastav, Rupendra Sahu,}, year={2021}, month={Sep.}, pages={2485-2496} }