Alert on Mask Detection System – Students Research in ML and DL at Durham College

Share

As a result of the fast development and spread of the COVID-19 pandemic throughout the world, people's everyday lives have been severely disrupted in recent times. One proposal for controlling the epidemic is to make individuals wear face masks in public. As a result, we require face detection systems that are both automated and efficient for such enforcement. We propose a face mask identification model for static and real-time videos in this research, and the pictures are classified as "with mask" or "without a mask." The model uses a Kaggle dataset to train and test. The collected data set contains over 10,000 images (considering 5,000 with mask and similarly 5,000 without) and has a 98 percent performance accuracy rate. The proposed model is computationally efficient and precise compared to Haar-Cascade & ANN. The application of this research are various, including digitized scanning tool in schools, hospitals, banks, airports, and many other public or commercial locations.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 07 May 2022
  • Time: 06:00 PM to 07:00 PM
  • All times are (GMT-05:00) Canada/Eastern
  • Add_To_Calendar_icon Add Event to Calendar

Join Zoom Meeting

https://durhamcollege-ca.zoom.us/j/94279982975

  • Toronto, Ontario
  • Canada



  Speakers

Henil Shah

Topic:

Alert on Mask Detection System – Students Research in ML and DL at Durham College

Speakers: Henil Shah, Neenu Markose

Email: