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ECG-based biometric human identification based on backpropagation neural network
conference contribution
posted on 2023-05-23, 13:46 authored by Lynn, HM, Soonja YeomSoonja Yeom, Kim, PBiometric human identifications are expansively reshaping security applications in the emerging sophisticated era of smart devices. To inflate the level of security and privacy demands, human physiological signal based human identification and authentication systems are getting tremendous attention. This study focuses on producing feasible amount of segmented signals from a source signal for training dataset, and integrating 2-layer framework backpropagation neural network to handle the great amount of classes for identification without hesitation. The results suggest that the proposed method surpasses the recent technique with the similar architecture, and possesses more advantages in terms of computational complexity and high performance compared with the previously reported study.
History
Publication title
Proceedings of the 2018 Conference on Research in Adaptive and Convergent SystemsPagination
6-10ISBN
978-1-4503-5885-9Department/School
School of Information and Communication TechnologyPublisher
ACMPlace of publication
USAEvent title
2018 Conference on Research in Adaptive and Convergent Systems (RACS '18)Event Venue
Honolulu, HI, USADate of Event (Start Date)
2018-10-09Date of Event (End Date)
2018-10-12Rights statement
Copyright 2018 Association for Computing MachineryRepository Status
- Restricted