Classification and Localization of COVID-19 based on a Pneumonia Radiograph using a Deep Learning Approach

now, and even after 2 years of the COVID-19 pandemic, this technology
is still not reasonably advanced to tackle the battle against this
virus most efficiently. The total number of COVID-19 cases worldwide
surpassed 420 million, with 5.8 million deaths. COVID-19
infects a person with various symptoms, and one of the symptoms
is pneumonia. A person suffering from pneumonia may or may not
be carrying COVID-19. This research article aims to describe an
X-radiation (X-ray) of patients with pneumonia and proposes other
subjects who also have the corona virus. This system is based on
Deep Learning (DL), and the Convolutional Neural Networks (CNN)
method is applied. The work is done with additional help from the
frameworks Tensorflow and Keras. Firstly, the images are loaded
into the compiler, cleaned, and preprocessed accordingly. The next
thing to come up with is setting up the Neural Network (NN) layer.
The CNN layer is formed, and a particular Activation Function
(AF), Rectified Linear Unit (ReLu), is applied. Finally, the model
is trained, and a classification is done to determine whether the
patient’s X-ray is only for pneumonia or pneumonia + COVID-19.
The paper’s outcome has an accuracy of 96% to 98%.