Real time electrocardiogram identification with multi-modal machine learning algorithms
Weaknesses in conventional identification technologies such as identification cards, badges and RFID tags prompts attention to biometric form of identification. Biometrics like voice, brain signal and finger print are unique human traits that can be used for identification. In this paper we prese...
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Main Authors: | , , , , |
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Format: | Conference or Workshop Item |
Language: | English English |
Published: |
Springer International Publishing
2017
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Online Access: | http://irep.iium.edu.my/60819/1/60819_Real%20time%20electrocardiogram%20identification%20with%20multi-modal.pdf http://irep.iium.edu.my/60819/7/60819_Real%20time%20electrocardiogram%20identification%20with%20multi-modal_WOS.pdf http://irep.iium.edu.my/60819/ https://link.springer.com/chapter/10.1007/978-3-319-59427-9_48 |
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http://irep.iium.edu.my/60819/1/60819_Real%20time%20electrocardiogram%20identification%20with%20multi-modal.pdfhttp://irep.iium.edu.my/60819/7/60819_Real%20time%20electrocardiogram%20identification%20with%20multi-modal_WOS.pdf
http://irep.iium.edu.my/60819/
https://link.springer.com/chapter/10.1007/978-3-319-59427-9_48