자료유형 | 학위논문 |
---|---|
서명/저자사항 | A Framework for Combining Ancillary Information with Primary Biometric Traits. |
개인저자 | Ding, Yaohui. |
단체저자명 | Michigan State University. Computer Science - Doctor of Philosophy. |
발행사항 | [S.l.]: Michigan State University., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 181 p. |
기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
ISBN | 9780438208773 |
학위논문주기 | Thesis (Ph.D.)--Michigan State University, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Arun Ross. |
요약 | Biometric systems recognize individuals based on their biological attributes such as faces, fingerprints and iris. However, in several scenarios, additional ancillary information such as the biographic and demographic information of a user (e.g. |
요약 | The incorporation of ancillary information raises several challenges. Firstly, ancillary information such as gender, ethnicity and other demographic attributes lack distinctiveness and can be used to distinguish population groups rather than ind |
요약 | In this regard, this dissertation makes three contributions. The first contribution entails the design of a Bayesian Belief Network (BBN) to model the relationship between biometric scores and ancillary factors, and exploiting the ensuing struct |
요약 | In summary, this dissertation seeks to advance our understanding of systematically exploiting ancillary information in designing effective biometric recognition systems by developing and evaluating multiple statistical models. |
일반주제명 | Computer science. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |