TY - GEN
T1 - Using deep learning for COVID-19 control
T2 - 2021 International Conference on Smart Applications, Communications and Networking, SmartNets 2021
AU - Deery, Caolan
AU - Meehan, Kevin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/9/22
Y1 - 2021/9/22
N2 - The ongoing COVID-19 pandemic has changed people's lives in ways that many would not have predicted. In the days, weeks and months since mandatory lockdowns and restrictions came into effect worldwide, people have had to adjust their daily lives in an effort to slow and restrict the spread of the virus - like regularly sanitising their hands, maintaining social distancing in crowded places, and wearing facemasks. The latter is contentious for some but has been a necessary deterrent in slowing the spread of this virus. There is potential for utilising technology as a supplementary deterrent and monitoring tool to help detect non-compliance of mask wearing. This research investigates the efficacy of AI for such purposes, exploring the applicability of a Convolutional Neural Network (CNN), for predicting if a person in a real time video feed is wearing a facemask. A dataset of over 10, 000 images was created to effectively evaluate this research. The CNN developed was tested against the validation dataset to evaluate its performance, the model demonstrated 98.47% accuracy on a varied and balanced dataset.
AB - The ongoing COVID-19 pandemic has changed people's lives in ways that many would not have predicted. In the days, weeks and months since mandatory lockdowns and restrictions came into effect worldwide, people have had to adjust their daily lives in an effort to slow and restrict the spread of the virus - like regularly sanitising their hands, maintaining social distancing in crowded places, and wearing facemasks. The latter is contentious for some but has been a necessary deterrent in slowing the spread of this virus. There is potential for utilising technology as a supplementary deterrent and monitoring tool to help detect non-compliance of mask wearing. This research investigates the efficacy of AI for such purposes, exploring the applicability of a Convolutional Neural Network (CNN), for predicting if a person in a real time video feed is wearing a facemask. A dataset of over 10, 000 images was created to effectively evaluate this research. The CNN developed was tested against the validation dataset to evaluate its performance, the model demonstrated 98.47% accuracy on a varied and balanced dataset.
KW - COVID-19
KW - Computer Vision
KW - Convolutional Neural Network
KW - Deep Learning
KW - Face Detection
KW - Facemask
UR - http://www.scopus.com/inward/record.url?scp=85117378195&partnerID=8YFLogxK
U2 - 10.1109/SmartNets50376.2021.9555431
DO - 10.1109/SmartNets50376.2021.9555431
M3 - Conference contribution
AN - SCOPUS:85117378195
T3 - 2021 International Conference on Smart Applications, Communications and Networking, SmartNets 2021
BT - 2021 International Conference on Smart Applications, Communications and Networking, SmartNets 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 September 2021 through 24 September 2021
ER -