COVID-19 is a crisis with numerous casualties. The World Health Organization (WHO) has declared the use of masks as an essential safety measure during the COVID-19 pandemic. Therefore, whether or not to wear a mask is an important issue when entering and exiting public places and institutions. However, this makes face recognition a very difficult task because certain parts of the face are hidden. As a result, face identification and identity verification in the access system became difficult. In this paper, we propose a system that can detect masked face using transfer learning of Yolov5s and recognize the user using transfer learning of Facenet. Transfer learning preforms by changing the learning rate, epoch, and batch size, their results are evaluated, and the best model is selected as representative model. It has been confirmed that the proposed model is good at detecting masked face and masked face recognition.
목차
Abstract 1. INTRODUCTION 2. RELATED WORKS 2.1 YOLOv5 2.2 Facenet[5] 3. METHODOLGY 3.1 Masked face detection experiment and result analysis 3.2 Masked face recognition experiment and result analysis 4. CONCLUSION REFERENCES
키워드
Masked Face DetectionMask DetectionObject DetectionYoloMasked Face Recognition
저자
NaeJoung Kwak [ Prof., Dept. of Cyber and Security , Baejae Univ., Korea ]
DongJu Kim [ Professor, Postech Institute of Artificial Intelligence, POSTECH ]
Corresponding Author
국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
설립연도
2009
분야
공학>공학일반
소개
본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.
간행물
간행물명
International Journal of Advanced Culture Technology(IJACT)
간기
계간
pISSN
2288-7202
eISSN
2288-7318
수록기간
2013~2025
등재여부
KCI 등재
십진분류
KDC 600DDC 700
이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 10 Number 1