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AJRSP follows academic conditions and rules for the arbitration and dissemination of scientific research. All published articles have undergone a rigorous peer-review process based on initial screening and final decision.
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COVIDetect (A Deep Neural Network for Detecting COVID-19 Cases from Chest CT-scan Images)Authors: Md. Mobarak Hossain(1) , Muhammad Usama Islam(2*), Dr. Mohammod Abul Kashem(3) | Bangladesh Email: usamaislam@iut-dhaka.eduPh.D. Researcher in Media, Certified International Trainer in Sustainability Applications, (Qatar Chamber), Qatar
Abstract: Coronavirus (COVID) has claimed numerous lives since its outbreak in late 2019. It is estimated that around 72 million people are affected by the virus and a toll on human life has reached 1.6 millions as of December 2020 making it one of the worst pandemic in recorded history. Having understood the importance of the pandemic, we devised a deep neural network model to classify COVID patients from non-COVID patients based on computerized tomography (CT) scan images with an accuracy of 76.5% that concluded our contribution to the growing pandemic. Keywords: COVID-19, Coronavirus, Image Processing, Deep learning, Neural Network Download PDF |