인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
피인용 0
초록·키워드
Face-recognition using deep-learning techniques typically face problems with learning about angles and with flexibility. In this study, we propose a face recognition system specialized for angles by using gray images. The K-face dataset was used to perform learning, along with triplet loss to achieve angle-specific learning. We reconstructed the model structure of Inceptionresnetv2, a model with excellent face recognition performance and the proposed model achieved an accuracy of approximately 96.9 %. In addition, the performance verification for each illuminance and angle was conducted and showed that the proposed model was flexible to the angle and illuminance. To confirm the applicability of model in the real environment, 21 subjects were recruited and verified. Transfer learning was performed to ensure the flexibility of the model in the real environment and gray images were used to reduce the effect of illuminance. Consequently, we obtained approximately 81% of the results and it was demonstrated that the proposed face recognition system can be applied in a real environment.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-090985237
