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Face and Fingerprint Fusion Using Deep Learning
Ekal S., Wadke K., Altamash M.,
Published in Springer Science and Business Media Deutschland GmbH
2023
Volume: 959
   
Pages: 155 - 164
Abstract
Biometrics recognition for individuals has been flourishing over the past few years, with the introduction of these systems in almost every sector of various industries. It makes keeping a track of large numbers of people easier at the administration level, eliminating the requirement of manual checks for every individual. Biometrics traits are individual characteristics like fingerprint, face, voice, etc., on the basis of which individuals are identified. Biometric technology and its use is not only limited to its application as a verification tool but also goes beyond that. Due to its secure, powerful and distinctive capabilities, its applications can also be extended as credentials tools and also digital authentication measures. The growth and pace of development in biometrics technology have been tremendous over the past few years and is considered to grow faster in the coming decades. The framework of the proposed model consists of performing feature-level fusion with the dataset used, and the second half consists of using various deep learning models to classify the labels correctly according to the original dataset. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About the journal
JournalLecture Notes in Electrical Engineering
PublisherSpringer Science and Business Media Deutschland GmbH
ISSN18761100
Open AccessNo