Project Info

Project Id:11785

Face mask detection using CNN The rise of the coronavirus globally has necessitated wearing face masks as a regulation to safeguard from contracting the virus. As COVID-19 has been proven to be transmitted predominantly through airdrops, wearing a mask has become a prerequisite to combat the spread of the virus Computer vision is one of the emerging frameworks in the field of object detection and is widely being used in various aspects of research in artificial intelligence. There have been both supervised and unsupervised approaches of machine learning in the past for object detection in an image.e a new convolutional neural network architecture called MobileNet Convolutional Neural Network, a very effective feature extractor for object detection that works well with mobile models. The neural network is first trained using the available dataset to create a model for classifying masked and unmasked faces in the image. The trained cascade classifier will find out if the person is wearing a mask or not.This model has provided a highest accuracy of all other modelswith accuracy of 99%.

• Model detects masks with images/videos
• Provides Highest Accuracy of 99%
• CLI based User Interface