Development of Iris Recognition System Using Enhanced Convolution Neural Network

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dc.contributor.advisorDr. Adegoke M.A.
dc.contributor.authorADEGBOYE, Olujoba James
dc.date.accessioned2026-08-31T11:16:30Z
dc.date.available2026-08-31T11:16:30Z
dc.date.issued2020-09-21
dc.descriptionXi.100pages.;illustration.hardback
dc.description.abstractBiometric traits such as face, iris, voice, fingerprint, and palm print have proved to be unique to each person and constant throughout its lifetime. Among all biometric characteristics, iris patterns have been revealed as one of the most reliable biometric traits to distinguish among different persons. Iris recognition is usually known as eye iris network pattern recognition technology, iris, more reliable and state for identification because iris is a unique feature which h does not change with age it remains stable and fixed from about one year of age throughout life. This research work developed an enhanced convolution neural network-based systems to recognize features. The enhancement was done using gravitational search algorithm (GSA).
dc.identifier.urihttps://ir.bellsuniversity.edu.ng/handle/123456789/605
dc.language.isoen
dc.publisherBells University of Technology, Ota.
dc.subjectChinese academy
dc.subjectFalse posistive
dc.subjectFalse negative
dc.titleDevelopment of Iris Recognition System Using Enhanced Convolution Neural Network
dc.typeDissertation

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