Pneumonia is an inflammatory lung disease which mainly affects the small air sacs known as alveoli. Symptoms of Pneumonia usually involves a mixture of painful or dry cough, chest discomfort, fatigue and difficulties in breathing. So, symptoms of pneumonia can be detected using chest x-rays. Since chest x-rays plays an important role in the detection of pneumonia a deep learning approach can be used for the detection in order to automate it. In this paper the implementation of deep learning approach for the chest x-rays is proposed. This approach has three convolution layers each with 32 neurons with three different channels (3*3). In order to obtain a more robust accuracy, images are transformed based on various parameters. Experimental analysis validates the accuracy of proposed model as 88.68%. The training accuracy and validation accuracy of the model in each epoch is analysed and observed as comparatively high than conventional process.
Deep Learning Approach to detect Pneumonia
05.11.2020
287863 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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