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All Journal International Journal of Electrical and Computer Engineering
Hazem W. Marar
Princess Sumaya University for Technology
Computer Science & IT Electrical & Electronics Engineering

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A 15-Gbps BiCMOS XNOR gate for fast recognition of COVID-19 in binarized neural networks Rosana W. Marar; Hazem W. Marar
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp997-1002

Abstract

The COVID-19 pandemic is spreading around the world causing more than 177 million cases and over 3.8 million deaths according to the European Centre for Disease Prevention and Control. The virus has devastating effects on economies, health, and well-being of worldwide population. Due to the high increase in daily cases, the available number of COVID-19 test kits in under-developed countries is scarce. Hence, it is vital to implement an effective screening method of patients using chest radiography since the equipment already exists. With the presence of automatic detection systems, any abnormalities in chest radiography that characterizes COVID-19 can be identified. Several artificial-intelligence algorithms have been proposed to detect the virus. However, neural networks training is considered to be time-consuming. Since computations in training neural networks are spent on floating-point multiplications, high computational power is required. Multipliers consume the most space and power among all arithmetic operators in deep neural networks. This paper proposes a 15 Gbps high-speed bipolar-complementary-metal-oxide-semiconductor (BiCMOS) exclusive-nor (XNOR) gate to replace multipliers in binarized neural networks. The proposed gate can be implemented on BiCMOS-based field-programmable gate arrays (FPGAs). This will significantly improve the response time in identifying chest abnormalities in CT scans and X-rays.
Co-Authors Rosana W. Marar