Nationality detection through Eye analysis

dc.contributor.authorShoumik, Shahib Islam
dc.date.accessioned2024-06-03T06:19:16Z
dc.date.available2024-06-03T06:19:16Z
dc.date.issued2024-01-01
dc.description.abstractBiometric identification has become increasingly popular as technology progresses, especially with regard to facial and ocular recognition. The study investigates the use of deep learning methods more especially, the VGG-19 model in the analysis of eye pictures with the goal of identifying nationality. Five different classes representing the perspectives of people from Bangladesh, Vietnam, South Korea, China, and South Korea are the subject of the study. The dataset is made up of a small range of carefully selected high resolution eye pictures that accurately depict each nationality. A deep learning model is trained to identify minute patterns and features in the eye pictures that differentiate people from the aforementioned ethnicities using the VGG-19 architecture. By means of extensive testing and optimization, our model attains a remarkable level of precision.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12610
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12610
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectBiometric Identification
dc.subjectVGG-19
dc.subjectEye Pictures
dc.subjectNationality Detection
dc.subjectImage processing
dc.subjectDeep Learning
dc.subjectEye Characteristics
dc.titleNationality detection through Eye analysis
dc.typeOther

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