ABSTRACT
Over numerous nations on earth, a brand-new virus known as the corona virus has been spreading like wildfire. Hospitals are exposed to many people, and it might be difficult to follow COVID-19 and take into consideration all patients. We have created a decision-making method based on a few parameters and X-rays to identify the priority of patients. The Mask R- CNN technique is used to train and test on the dataset to classify patients as having COVID infection or not. On chest X-ray pictures, the mask R CNN technique enhances COVID - 19 detection performance. © 2022 IEEE.
ABSTRACT
Corona pandemic has affected the daily routine of life disturbing the trade and economic globally. Wearing a mask has become compulsory and a new tradition. within the close to future, several suppliers can raise the shoppers to wear masks properly. Therefore, detection of face mask has become one of the important tasks to assist the international society. This paper provides a easy and simplified approach to detect the face masks using some of the important Machine Learning packages like TensorFlow, Keras, OpenCV and Scikit-Learn. The projected methodology detects the face from the image properly and so identifies if it's a mask thereon or not. As a police work task performing artist, it may detect a face together with a mask in motion. the tactic gives an accurate output with an accuracy of 96.77% on dataset. The model tendency to find the optimized values of parameters are employed using Convolutional Neural Network (CNN) model to identify whether the masks are worn properly or not while not inflicting over-fitting. © 2021 IEEE.