International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1712
No. of Authors : 4737
  Journal Paper


Paper Title :
Advanced Deep Learning Application in Covid-19 Detection from X-Rays Images

Author :Tabindha Farah Khan Qurashie, Amit Kant Pandit

Article Citation :Tabindha Farah Khan Qurashie ,Amit Kant Pandit , (2022 ) " Advanced Deep Learning Application in Covid-19 Detection from X-Rays Images " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 10-16, Volume-10,Issue-7

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)

Type : Research paper

Published : Volume-10,Issue-7


DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-18911   View Here

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