Deep Convolutional Neural Network with Image Processing Techniques and Resnet252v2 for Detection of Covid19 from X-Ray Images
Keywords:Chest roentgen rays images, Convolutional Neural Networks, Coronavirus, COVID-19, SARS-CoV-2, Deep Learning, ResNet50, ResNet15V2
AbstractThe 2019 coronavirus disease, also known as SARS-CoV-2, has emerged as a highly contagious viral infection with a significant global impact. It has rapidly spread across various regions, resulting in a substantial number of individuals being affected by this disease. Research findings indicate that the rapid and widespread transmission of the disease has posed significant challenges for healthcare professionals in promptly diagnosing the condition and implementing effective measures to contain its propagation. The automation of the diagnostic procedure has emerged as a critical necessity. According to research findings, the implementation of this particular measure has been shown to significantly enhance work efficiency while simultaneously safeguarding healthcare workers from potential exposure to harmful viruses. Medical image analysis is a rapidly growing area of research that offers a promising solution to address this problem with greater precision. This research paper introduces a novel approach for predicting SARS-CoV-2 infection using chest radiography images...
Copyright (c) 2023 Kavitha Rajalakshmi D, Bharathisindhu P
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