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dc.contributor.authorAbdul-Al, Mohamed
dc.contributor.authorKyeremeh, George K.
dc.contributor.authorOjaroudi Parchin, Naser
dc.contributor.authorAbd-Alhameed, Raed
dc.contributor.authorQahwaji, Rami S.R.
dc.contributor.authorRodriguez, J.
dc.date.accessioned2021-12-15T09:53:06Z
dc.date.available2021-12-15T09:53:06Z
dc.date.issued2021-10-27
dc.identifier.citationAbdul-Al M, Abd-Alhameed R, Kyeremeh GK et al (2021) IEEE 26th International Workshop on Computer-Aided Modeling and Design of Communication Links and Networks (CAMAD) 25-27 Oct 2021. Porto, Portugal.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18682
dc.descriptionYesen_US
dc.description.abstractBiometric authentication is the science and engineering of assessing and evaluating bioinformatics from the human body in order to increase system security by providing reliable and accurate behaviors and classifiers for personal identification and authentication. Its solutions are widely used in industries, governments, and the military. This paper reviews the multimodal biometric systems that integrated both faces and fingerprints as well as shows which one has the best accuracy and hardware complexity with the methods and databases. Several methods have been used in multimodal biometric systems such as KNN (K-Nearest Neighbor), CNN (Convolutional Neural Network), PCA (Principal Component Analysis), and so on. A multimodal biometric system for face and fingerprints that uses an FoM (Figure of Merit) to compare and show between the articles the best accuracy that have used multimodal biometric system face and fingerprints methods. The best performance has been found is 99.43% by using the cascade multimodal method.en_US
dc.description.sponsorshipHorizon-MSCA-RISE-2019-2023, Marie Sklodowska-Curieen_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1109/CAMAD52502.2021.9617766en_US
dc.rights© 2021 IEEE. Reproduced in accordance with the publisher's self-archiving policy.en_US
dc.subjectMultimodalen_US
dc.subjectBiometricen_US
dc.subjectFaceen_US
dc.subjectFingerprinten_US
dc.titlePerformance of Multimodal Biometric Systems Using Face and Fingerprint (Short Survey)en_US
dc.status.refereedYesen_US
dc.typeConference paperen_US
dc.type.versionAccepted manuscripten_US
refterms.dateFOA2021-12-15T09:55:21Z
dc.openaccess.statusopenAccessen_US


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