TY - GEN
T1 - Covid-19 Mask Detector Based on YOLO and MATLAB
AU - Pradika Napitupulu, Haposan Yoga
AU - Sudiana, Dodi
N1 - Funding Information:
Deepest gratitude to Indonesia Endowment Funds for Education (LPDP) for supporting this research.
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Coronavirus Disease 2019, known as Covid-19 has spread in the world for the past three years. Even though it has been three years, the pandemic has not over yet, some people are still infected despite the have already vaccinated. Coronavirus is the virus which responsible for the disease can spread rapidly. To stop human-to-human transmission of the virus, WHO and Government urged people to wear the protective equipment such as mask. However, some people are reluctant to wear them, it can cause coronavirus spread and make some people get infected. In this paper, we developed a system to detect people who wearing mask or who not wearing mask. The system is divided into three sub system, the first one is to detect people who wearing mask or who not wearing mask on picture, the second one is to detect people who wearing mask or who not wearing mask on video, and the last one is to detect people who wearing mask or who not wearing mask via web cam (video real-time). The program can detect person who wear several types of masks, including light and dark masks with accuracy 92,8523%. The system was developed based on YOLO and MATLAB.
AB - Coronavirus Disease 2019, known as Covid-19 has spread in the world for the past three years. Even though it has been three years, the pandemic has not over yet, some people are still infected despite the have already vaccinated. Coronavirus is the virus which responsible for the disease can spread rapidly. To stop human-to-human transmission of the virus, WHO and Government urged people to wear the protective equipment such as mask. However, some people are reluctant to wear them, it can cause coronavirus spread and make some people get infected. In this paper, we developed a system to detect people who wearing mask or who not wearing mask. The system is divided into three sub system, the first one is to detect people who wearing mask or who not wearing mask on picture, the second one is to detect people who wearing mask or who not wearing mask on video, and the last one is to detect people who wearing mask or who not wearing mask via web cam (video real-time). The program can detect person who wear several types of masks, including light and dark masks with accuracy 92,8523%. The system was developed based on YOLO and MATLAB.
KW - COVID-19
KW - Detector
KW - Mask
KW - MATLAB
KW - YOLO
UR - http://www.scopus.com/inward/record.url?scp=85163133240&partnerID=8YFLogxK
U2 - 10.1109/ICCoSITE57641.2023.10127764
DO - 10.1109/ICCoSITE57641.2023.10127764
M3 - Conference contribution
AN - SCOPUS:85163133240
T3 - ICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering: Digital Transformation Strategy in Facing the VUCA and TUNA Era
SP - 200
EP - 205
BT - ICCoSITE 2023 - International Conference on Computer Science, Information Technology and Engineering
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Computer Science, Information Technology and Engineering, ICCoSITE 2023
Y2 - 16 February 2023
ER -