Effective Early Stage Detection of COVID-19 Using Deep Learning

Abstract

The Corona virus Disease 2019 (COVID-19), which was formerly called as 2019 Novel Corona Virus[1] is a breath taking disease. It had its impact on millions of lives across the world. At present, as of March 2021, the rate of infection has declined throughout different parts of the world [2]. But it has been warned by scientists that this deadly disease can have its second wave over a period of time. Also, there is a possibility of this covid-19 to become a seasonal disease [3]. In such case, premature diagnosis of this virus is essential in order to save many lives. A kit called RT-PCR has been employed to detect the presence of this virus [4]. However, this method of prognosis takes time depending on the locality of the infected person [5]. This leads to the proliferation of the infection. Hence, an alternate procedure should be unearthed, which diagnose this disease within a short span of time. In this paper, a Deep Learning concept has been proposed which aids the timely detection of the corona virus infection. This, inturn reduces the spreading rate of the infection and decreases mortality rate.

Artificial intelligence-powered intelligent reflecting surface systems countering adversarial attacks in machine learning

“…In this article, an AI-IRS system is proposed for next generation networks to reduce the vulnerability to a minimum level in the academic and business environment [7], [8]. This involves: i) calculating the susceptibilities of the AI methods of the IRS system by the adversarial attacks using fast gradient sign method (FGSM) and basic iterative method (BIM); ii) proposing a defensive distillation mitigation algorithm to improve the robustness and efficiency of the AI-model on the IRS system; and iii) training the AI-IRS systems to produce and maintain robust output data under undefended and defended methods using FGSM and BIM adversarial attacks.…”