Selected article for: "class covid and convolutional neural network"
Author: Rahul Kumar; Ridhi Arora; Vipul Bansal; Vinodh J Sahayasheela; Himanshu Buckchash; Javed Imran; Narayanan Narayanan; Ganesh N Pandian; Balasubramanian Raman
Title: Accurate Prediction of COVID-19 using Chest X-Ray Images through Deep Feature Learning model with SMOTE and Machine Learning Classifiers
  • Document date: 2020_4_17
    • ID: 59ghorzf_6
    Snippet: In another study, Sethy et al. 21 used chest x-ray images to recognize COVID viral infection, firstly they have extracted deep features using CNN based on pre-trained ImageNETand at the last layer SVM were used in order to classify it. In addition, Wang et al. 16 presented multi-class classification, deep convolutional neural network architecture named as COVID-Net implemented over 16, 756 chest radiography images that have been scanned with 13,6.....
    Document: In another study, Sethy et al. 21 used chest x-ray images to recognize COVID viral infection, firstly they have extracted deep features using CNN based on pre-trained ImageNETand at the last layer SVM were used in order to classify it. In addition, Wang et al. 16 presented multi-class classification, deep convolutional neural network architecture named as COVID-Net implemented over 16, 756 chest radiography images that have been scanned with 13,645 patient to classify the COVID-19 and non-COVID also with a safe and bacterial infected patient.

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