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- W4376141317 abstract "Coronavirus Disease 2019 (COVID-19) has led to a global pandemic in the year 2020 and the cases are dynamically increasing and active all over the world. COVID-19 is caused due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is a human-to-human transmissible disease which has severely affected people especially with weaker immunity, and is detected through Reverse Transcription Polymerase Chain Reaction (RT-PCR). RT-PCR is a lethargic process and therefore intelligent systems are proposed which uses chest images for early detection of COVID-19. This paper proposes a regularized and attentive intelligent system called ‘Mixed Attention & Regularized COVID-19 Network (MARCOV19-Net)’ for detection of COVID-19 using chest X-Ray images. The performance of MARCOV19-Net is compared with VGG-16, Regularized COVID-19 Deep Convolutional Network (RCOV19-DCNet) and Mixed Attention and unregularized COVID-19 Network (MACOV19-Net), and with other state-of-the-art models. MARCOV19-Net has achieved the highest F-score, ROC and AUC of 98.76%, 99.4% and 99.6%, respectively." @default.
- W4376141317 created "2023-05-12" @default.
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- W4376141317 date "2023-05-10" @default.
- W4376141317 modified "2023-10-17" @default.
- W4376141317 title "Mixed attention and regularized <scp>COVID</scp>‐19 network: An approach to detection of <scp>COVID</scp>‐19 with chest <scp>x‐ray</scp> images" @default.
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- W4376141317 doi "https://doi.org/10.1002/ima.22903" @default.
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