DOIONLINE 
DOIONLINE Publish In |
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC |
 Journal Home Volume Issue |
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Issue |
Volume-10,Issue-7 ( Jul, 2022 ) | |||||||||
Paper Title |
Advanced Deep Learning Application in Covid-19 Detection from X-Rays Images | |||||||||
Author Name |
Tabindha Farah Khan Qurashie, Amit Kant Pandit | |||||||||
Affilition |
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Pages |
10-16 | |||||||||
Abstract |
Abstract - Globally, the exponential increase in Covid-19 patients is overwhelming healthcare systems. Variety of methods are devised for early detection of infected cases especially the chest x-ray imaging. Our study uses new Convolutional Neural Network model with 7154 images of affected and non-affected cases. We follows an image pre-handling stage with image enhancement technique for training and generating a trustworthy image dataset to test and upgrade a deep learning algorithm models. Further, to extract deep features, we used pretrained deep CNN (Convolutional neural network) model. Moreover, the Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) has been used for further extraction. Our analysis reflected the presence of Covid-19 infection with high accuracy and sensitivity. Keywords - COVID-19; Deep Learning; Chest x-ray images; Convolutional Neural Network models; Image processing; Support Vector Machine (SVM) | |||||||||
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