Face Mask Detection under the Threat of Covid-19 Virus

For wearing a mask, Covid19 has a new identity. Detecting masked faces with accuracy and efficiency is becoming increasingly important. Face mask recognition is a tough task because of the high occlusions that cause the loss of face in-formation. Furthermore, There aren't many large-scale, masked face with a well-label datasets out there, which makes face mask recognition more difficult. CNN-based deep learning algorithms have achieved significant advances in a variety, one aspect of computer vision is face detection disciplines. We introduce a new cascade structure based on CNN for recognising face masks in this paper, This is made up of three convolutional neural networks that have been successfully built. To finetune our CNN models, we propose a new dataset named “facial mask dataset.” due to a paucity of face masked training instances. Face masks were tested on a set of faces, we assess our suggested face mask recognition algorithm, and it performs admirably. A new cascade framework based on CNN is proposed for detecting face masks and their types, which comprises of three properly built convolutional neural networks.