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dc.contributor.authorHarish, B S
dc.contributor.authorMaheshan, M S
dc.contributor.authorNagadarshan, N
dc.date2020-03
dc.date.accessioned2022-03-21T09:18:49Z
dc.date.available2022-03-21T09:18:49Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/12692
dc.description.abstractThe world is shifting to the digital era in an enormous pace. This rise in the digital technology has created plenty of applications in the digital space, which demands a secured environment for transacting and authenticating the genuineness of end users. Biometric systems and its applications has seen great potentials in its usability in the tech industries. Among various biometric traits, sclera trait is attracting researchers from experimenting and exploring its characteristics for recognition systems. This paper, which is first of its kind, explores the power of Convolution Neural Network (CNN) for sclera recognition by developing a neural model that trains its neural engine for a recognition system. To do so, the proposed work uses the standard benchmark dataset called Sclera Segmentation and Recognition Benchmarking Competition (SSRBC 2015) dataset, which comprises of 734 images which are captured at different viewing angles from 30 different classes. The proposed methodology results showcases the potential of neural learning towards sclera recognition system.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 6, nº 1
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2715es_ES
dc.rightsopenAccesses_ES
dc.subjectbiometryes_ES
dc.subjectdeep learninges_ES
dc.subjectconvolutional neural network (CNN)es_ES
dc.subjectsclera recognitiones_ES
dc.subjectIJIMAIes_ES
dc.titleA Convolution Neural Network Engine for Sclera Recognitiones_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2019.03.006


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