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dc.contributor.authorLin, Wen-Huien_US
dc.contributor.authorWang, Pingen_US
dc.contributor.authorWu, Bao-Huaen_US
dc.contributor.authorChao, Kuo-Mingen_US
dc.contributor.authorLo, Chi-Chunen_US
dc.date.accessioned2019-04-02T06:04:23Z-
dc.date.available2019-04-02T06:04:23Z-
dc.date.issued2018-01-01en_US
dc.identifier.urihttp://dx.doi.org/10.1109/ICEBE.2018.00023en_US
dc.identifier.urihttp://hdl.handle.net/11536/151088-
dc.description.abstractMobile commerce security needs quality services where mobile devices respond in real-time and traditional cloud computing approach uses a centralized architecture does not support these systems with such time dependency well. Thus, this study proposes a cross-age face-recognition model with MobileNets to determine the identity of a user in the situation of aging appearance change on a fog computing architecture. Especially, this study uses a face-recognition technique based on a distributed concept. In this concept, MobileNet-based face recognition system effectively performs cross-age face recognition for identity authentication with the enhanced facial features of the users locally. Overall, the MobileNet model reaches acceptable prediction accuracy with lower latency in face recognition process compared with that of the existing CNNs schemes.en_US
dc.language.isoen_USen_US
dc.subjectcross-age face recognitionen_US
dc.subjectuser authenticationen_US
dc.subjectfog computing architectureen_US
dc.subjectMobileNetsen_US
dc.subjectconvolutional neuron networksen_US
dc.titleA Cross-age Face Recognition Approach Using Fog Computing Architecture for User Authentication on Mobile Devicesen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/ICEBE.2018.00023en_US
dc.identifier.journal2018 IEEE 15TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE 2018)en_US
dc.citation.spage86en_US
dc.citation.epage93en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000459615100012en_US
dc.citation.woscount0en_US
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