ABSTRACT
Covid-19 is a novel pandemic disease with no potential vaccine treatment or medicine, the world is facing currently as of now. The death toll has increased to several lakhs and recovery rate is comparatively very less, was initially spotted in Wuhan (China). This spreads through close contact with people and socializing. The number of infected people varies with different parts of the world In our particular country India we are going through the lock down period which is the only vaccine to promote "social distancing" The hurdle arose due to the widespread of corona is major economy loss in combo with innocent lives. In this manuscript, we are visualizing the dataset which is publicly available to map, differentiate and separate the data in order to segregate the places that are most prone and perform basic regression to identify and predict the increasability of the counts from the dataset.
ABSTRACT
Covid-19 is a novel pandemic disease with no potential vaccine treatment or medicine, the world is facing currently as of now. The death toll has increased to several lakhs and recovery rate is comparatively very less, was initially spotted in Wuhan (China). This spreads through close contact with people and socializing. The number of infected people varies with different parts of the world In our particular country India we are going through the lock down period which is the only vaccine to promote “social distancing” The hurdle arose due to the widespread of corona is major economy loss in combo with innocent lives. In this manuscript, we are visualizing the dataset which is publicly available to map, differentiate and separate the data in order to segregate the places that are most prone and perform basic regression to identify and predict the increasability of the counts from the dataset.
ABSTRACT
COVID-19 pandemic has led to an international health emergency the WHO considers wearing a face mask an appropriate form of public health protection. This work will describe a face mask identification model that incorporates both deep and traditional machine learning techniques. Parts of the suggested model can be divided into two. Using Resnet50, the initial part of the system is set up for feature extraction. The second component classifies face masks using decision trees, support vector machines (SVMs), and the ensemble approach. The research will focus on three face-masked datasets. The Real-World Masked Face Dataset Includes three datasets: real-world masked faces, simulated faces, and wild faces (LFW). 99.64% of RMFD's SVM classifier is accurate throughout testing.. It achieved a 99.49% accuracy rate in SMFD and a 100% accuracy rate in LFW. © 2022 IEEE.
ABSTRACT
An outbreak of severe acute respiratory disease due to a novel corona virus was reported from the city of Wuhan, Hubei Province, China in December 2019. Initially named as novel coronavirus 2019 (2019-nCoV), the virus was later officially named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2). The disease caused by it was officially named by the World Health Organization as Corona Virus Disease 2019(COVID-19). Within a short span of time the epidemic spread to all provinces of China and 68 other countries and caused more than 80, 000 confirmed Infections and over 3000 (as on 6th March, 2020) deaths. 33 cases were confirmed in India and several suspected cases quarantined. In this review article, the origin of the virus, its genetic make-up, and how the epidemic evolved are discussed. The spectrum of clinical features, important laboratory and imaging findings as per early clinical studies are described In detail. The current treatment principles along with the future prospects of treatment are outlined. Preventive measures taken are narrated. The possible future scenarios of the epidemic are depicted.