Comparative analysis of the effectiveness of ML and DL techniques for classifying Face Masks
Junianto Chandra Kusuma, Peeta Basa Pati · 2023
In 2020, COVID has grown to be a significant public health concern. The virus's contact-transparent properties caused it to propagate quickly. Wearing a mask that stops the transmission is the most effective strategy to prevent this. The first step in lowering the danger is to wear a mask, which cuts the likelihood of contracting the infection by 70%. To resolve this problem, we need the system to keep an eye on the facial mask. This work can be facilitated by a face mask detector based on deep learning (DL) and machine learning (ML) models can make this task easier. Here, we do face mask categorization utilizing several ML and DL techniques. Here, we experimented with various methods such as CNN, Resnet50, Gabor filter, GLCM, SVM, KNN for extracting features and classifying faces with mask and without mask. From the accuracy we got for each model it says CNN performs well on the dataset we took.