ABSTRACT
COVID-19 has become a global crisis. During such a time of adversity, it has become difficult to create safe working conditions for people resulting in a lack of workforce for performing a multitude of tasks. As a result, there is a requirement for “next-gen” autonomous systems to perform various tasks. One of the reasons why humans are efficient in doing a lot of tasks is the ability to detect and distinguish between various objects around them and proceed with doing the intended task further. Object detection methods are designed to replicate this human behavior and can be used in various applications that serve to aid in the COVID-19 crisis. Object detection deals with identifying objects belonging to a predefined class in the image. This chapter aims at explaining the most commonly used methods like region-based convolutional neural network and You Only Look Once of object detection along with a few of its applications. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
In this paper, we are predicting and forecasting the COVID-19 outbreak in India based on the machine learning approach, where we aim to determine the optimal regression model for an in-depth analysis of the novel Coronavirus in India. We are implementing the two regression models namely linear and polynomial and evaluating the two using the R squared score and error values. The COVID-19 dataset for India is being used to serve the research of this paper. The model is predicting the number of confirmed, recovered, and death cases based on the data available from March 12 to October 31,2020. For forecasting the future trend of these cases, we are utilizing the time series forecasting approach of tableau. Furthermore, the time series forecasting method is being employed to forecast the total count of confirmed cases in the future. © 2021 IEEE