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A beta coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was identified recently This virus caused pneumonia of unknown etiology and is named as Coronavirus Disease 2019 (COVID-19) The disease is novel and hence no medicine to cure the infected patients is available The only way to control the pandemic is by breaking the chain of the virus The chain can be broken by massive diagnosis and social distancing Radiological examinations, included computed tomography is identified as an effective way for disease diagnosis CT and Chest X-ray images are considered to be an effective way for making clinical decisions The X-ray facility is available even in the remotest parts and thus X-ray images can be easily acquired for patients These images can help in prevention of infection, diagnosis and control In this paper, an initial investigation report on the various aspects of COVID-19 is presented An automated method for diagnosis of COVID-19 from X-ray images is proposed The proposed model is based on XceptionNet that uses depth wise separable convolutions The results obtained from the proposed model have high accuracy The proposed method is compared with four other state of the art methods The comparative study reveals that the proposed method performs better than the existing methods Thus the method can be effectively used for diagnosis of the novel coronavirus
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Romanian_Journal_of_Information_Science_and_Technology
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Diagnosis of Coronavirus Disease (COVID-19) from Chest X-Ray images using modified XceptionNet
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