Deep Learning Based Indian Currency Detection for Visually Challenged using VGG16 | Zendy

Nijil Raj N | Zendy; Anandu S Ram | Zendy; Aneeta Binoo Joseph | Zendy; S Shabna | Zendy

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Deep Learning Based Indian Currency Detection for Visually Challenged using VGG16

Author(s) -

Nijil Raj N,

Anandu S Ram,

Aneeta Binoo Joseph,

S Shabna

Publication year - 2020

Publication title -

international journal of recent technology and engineering (ijrte)

Language(s) - English

Resource type - Journals

ISSN - 2277-3878

DOI - 10.35940/ijrte.b3955.079220

Subject(s) - banknote , deep learning , visually impaired , artificial intelligence , currency , convolutional neural network , computer science , convolution (computer science) , artificial neural network , human–computer interaction , economics , monetary economics

Banknote recognition is a major problem faced by visually Challenged people. So we propose a system to help the visually Challenged people to identify the different types of Indian currencies through deep learning technique. In our proposed project, bank notes with different positions are directly fed into VGG 16, a pretrained model of convolution neural network which extracts deep features. From our work the visually impaired people will be able to recognize different types if Indian Currencies.

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