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Nuts Types Classification Using Deep learning

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dc.contributor.author Dheir, Ibtesam M.
dc.contributor.author Abu Mettleq, Alaa Soliman
dc.contributor.author Elsharif, Abeer A.
dc.date.accessioned 2020-02-14T15:38:58Z
dc.date.available 2020-02-14T15:38:58Z
dc.date.issued 2020
dc.identifier.uri http://dspace.alazhar.edu.ps/xmlui/handle/123456789/567
dc.description.abstract Nuts are nutrient-dense foods with complex matrices rich in unsaturated fatty and other bioactive compounds. By virtue of their unique composition, all types of nuts are likely to beneficially impact health outcomes. In this paper, we classified five types of Nuts with a dataset that contains 2868 images. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used for this task. The trained model achieved an accuracy of 98% on a held-out test set, demonstrating the feasibility of this approach. en_US
dc.language.iso en_US en_US
dc.subject Deep Learning en_US
dc.subject Classification en_US
dc.subject Nuts en_US
dc.title Nuts Types Classification Using Deep learning en_US
dc.type Article en_US


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