DOIONLINE 
DOIONLINE Publish In |
International Journal of Soft Computing And Artificial Intelligence (IJSCAI)-IJSCAI |
 Journal Home Volume Issue |
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Issue |
Volume-10,Issue-1 ( May, 2022 ) | |||||||||
Paper Title |
Envision of Respiratory Disease using Convolutional Neural Network | |||||||||
Author Name |
Saurabh Kumar, Renu Dhir | |||||||||
Affilition |
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Pages |
22-29 | |||||||||
Abstract |
Abstract - A rise of respiratory problem among the mobs due to wide the spread of SARS-COV-2 leads to disease known as coronavirus. The common perspective of the spread is human contact. The efficient procedure need to be followed in the medical field to diagnose the disease. The Convolutional neural network, the subset of artificial intelligence together analysis and classify it using a dataset of chest X-radiation pictures. The convolutional neural architecture like ResNet50, VGG19, Inceptionv3 and Xception showed the accuracy 0.91, 0.98, 0.97 and 0.96 respectively in classifying the dataset into Covid-19 positive and Covid-19 negative. Keywords - Coronavirus, Artificial Intelligence, chest X-radiation, deep CNN, ResNet50, VGG19, Inceptionv3, Xception. | |||||||||
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