Monkey Pox Detection using Deep Learning
Simrin Fathima Syed, Arun Singh, Manik Rakhra, Dalwinder Singh, Shruti Aggarwal
Abstract
In this research article, the problem of detecting and identifying a new disease, referred to as “Monkey Pox,” is discussed. The widespread outbreak of the newly discovered disease that has been introduced has caused thousands of individuals to become ill and has even been linked to deaths. The effects of the disease might continue for up to three or fourweeks in a victim. In the present circumstances, there are no such methods that can analyse the sickness. In this research, we are going to work on the detection of this disease by employing a number of different Machine Learning models, such as Monkey Pox Skin Lession Datasets (MSLD), KNN Analysis, Ada Booster Classifier, Naive Bayes Classifier, and Decision Tree.