JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Classroom Roll-Call System Based on ResNet NetworksClassroom Roll-Call System Based on ResNet Networks |
| 영문제목(English Title) |
Classroom Roll-Call System Based on ResNet Networks |
| 저자(Author) |
Jinlong Zhu
Fanhua Yu
Guangjie Liu
Mingyu Sun
Dong Zhao
Qingtian Geng
Jinbo Su
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| 원문수록처(Citation) |
VOL 16 NO. 05 PP. 1145 ~ 1157 (2020. 10) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.
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| 키워드(Keyword) |
Face Recognition
Game
ResNet Networks
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| 파일첨부 |
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