ARTÍCULO
TITULO

Comparative Analysis of Image Classification Algorithms for Face Mask Detection

Mohammad Farid Naufal    
Selvia Ferdiana Kusuma    
Zefanya Ardya Prayuska    
Ang Alexander Yoshua    
Yohanes Albert Lauwoto    
Nicky Setyawan Dinata    
David Sugiarto    

Resumen

Background: The COVID-19 pandemic remains a problem in 2021. Health protocols are needed to prevent the spread, including wearing a face mask. Enforcing people to wear face masks is tiring. AI can be used to classify images for face mask detection. There are a lot of image classification algorithm for face mask detection, but there are still no studies that compare their performance.Objective: This study aims to compare the classification algorithms of classical machine learning. They are k-nearest neighbors (KNN), support vector machine (SVM), and a widely used deep learning algorithm for image classification which is convolutional neural network (CNN) for face masks detection.Methods: This study uses 5 and 3 cross-validation for assessing the performance of KNN, SVM, and CNN in face mask detection.Results: CNN has the best average performance with the accuracy of 0.9683 and average execution time of 2,507.802 seconds for classifying 3,725 faces with mask and 3,828 faces without mask images.Conclusion: For a large amount of image data, KNN and SVM can be used as temporary algorithms in face mask detection due to their faster execution times. At the same time, CNN can be trained to form a classification model. In this case, it is advisable to use CNN for classification because it has better performance than KNN and SVM. In the future, the classification model can be implemented for automatic alert system to detect and warn people who are not wearing face masks.  

 Artículos similares

       
 
Damny Magdaleno Guevara, Yadriel Miranda, Ivett Fuentes, María Garc ía     Pág. 69 - 80
A huge amount of information is represented in XML format. Several tools have been developed to store, and query XML data. It becomes inevitable to develop high performance techniques for efficiently analysing extremely large collections of XML data. O... ver más

 
Marcin Klosok, Daria Gendosz de Carrillo, Piotr Laszczyca, Tomasz Plociniczak, Halina Jedrzejowska-Szypulka and Tomasz Sawczyn    
Revista: Applied Sciences

 
Siarhei Autsou, Karolina Kudelina, Toomas Vaimann, Anton Rassõlkin and Ants Kallaste    
Servomotors have found widespread application in many areas, such as manufacturing, robotics, automation, and others. Thus, the control of servomotors is divided into various principles and methods, leading to a high diversity of control systems. This ar... ver más
Revista: Applied Sciences

 
Kristina Mazur, Mischa Saleh and Mirko Hornung    
Early and rapid environmental assessment of newly developed aircraft concepts is eminent in today?s climate debate. This can shorten the decision-making process and thus accelerate the entry into service of climate-friendly technologies. A holistic appro... ver más
Revista: Aerospace

 
Maryan Rizinski, Andrej Jankov, Vignesh Sankaradas, Eugene Pinsky, Igor Mishkovski and Dimitar Trajanov    
The task of company classification is traditionally performed using established standards, such as the Global Industry Classification Standard (GICS). However, these approaches heavily rely on laborious manual efforts by domain experts, resulting in slow... ver más
Revista: Information