A novel hybrid face mask detection approach using Transformer and convolutional neural network models.

ABSTRACT: Face and face mask detection are one of the most popular topics in computer vision literature. Face mask detection refers to the detection of people's faces in digital images and determining whether they are wearing a face mask. It can be of great benefit in different domains by ensuring public safety through the monitoring of face masks. Current research details a range of proposed face mask detection models, but most of them are mainly based on convolutional neural network models. These models have some drawbacks, such as their not being robust enough for low quality images and their being unable to capture long-range dependencies. These shortcomings can be overcome using transformer neural networks. Transformer is a type of deep learning that is based on the self-attention mechanism, an

SUBMITTER: Al-Sarrar HM 

PROVIDER: S-EPMC10280424 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature