What is it about?
During COVID-19, many places used or tested computer systems that can check whether someone is wearing a face mask. There are many different AI methods for this, and each one has strengths and weaknesses. Also, the information we have is not always clear or complete, so it can be hard to decide which method is best. In this paper, we introduce a new “fuzzy” math model (a way to handle uncertainty). It helps us describe unclear information and combine opinions or results in a consistent way. We then use this method to compare and rank different AI approaches for face mask detection. Our example shows how this can support choosing one approach in a clear and organized way.
Featured Image
Photo by jameson wu on Unsplash
Why is it important?
The main value of this work is that it gives a practical method for making decisions when the data is uncertain. Our approach can help researchers and decision-makers compare different options fairly, instead of relying on guesswork. While we tested it on face mask detection during COVID-19, the same idea can also be used in other areas where people must choose between several tools or technologies using incomplete or uncertain information.
Perspectives
I wanted this paper to be useful both in theory and in real life. It was interesting to take a new mathematical idea and show how it can help with a real problem from the COVID-19 period. I hope the method is helpful for other researchers who need to compare options and make decisions when the information is not perfectly certain.
Muhammad Danish Zia
National University of Sciences and Technology
Read the Original
This page is a summary of: A study of quadratic Diophantine fuzzy sets with structural properties and their application in face mask detection during COVID-19, AIMS Mathematics, January 2023, Tsinghua University Press,
DOI: 10.3934/math.2023738.
You can read the full text:
Resources
Contributors
The following have contributed to this page
