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- W4205583669 abstract "A coronavirus have a great impact on a public health globally. Real time PCR s used for pathological testing but that result in false test result this impact made to exploration of alternate method for testing [1]. The detection of coronavirus 2 using chest X-ray image is anlifesaving property. By using chest X-ray coronavirus can identified are cost effective and its available on every public health sector rural clinic hospital. Deep learning –based chest radiograph classification (DL-CRC) frame are used to distinguish the COVID-19 cases and normal cases will high accuracy. The pre-trained image database used for large training sets to have pre- trained weights .The training data consisting covid chest X-ray image and normal chest X-ray image and fed into customized convolution neural network (CNN) model in DL-CRC wear masks in public areas is a major protection for people .The classification implies that it can efficiently detection COVID-19 from radiograph image for provide a reliable and fast response of COVID-19 infection in the lung." @default.
- W4205583669 created "2022-01-25" @default.
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- W4205583669 date "2021-08-07" @default.
- W4205583669 modified "2023-09-30" @default.
- W4205583669 title "Novel Method for Detection of Sars-COV2 Using Chest X-Ray Images" @default.
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- W4205583669 doi "https://doi.org/10.48175/ijarsct-1821" @default.
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