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Authentication of bank notes and image processing through Artificial and Convolutional Neural Network

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dc.contributor.author Islam, Md. Touhidul
dc.date.accessioned 2018-08-06T09:22:04Z
dc.date.accessioned 2019-05-27T10:17:26Z
dc.date.available 2018-08-06T09:22:04Z
dc.date.available 2019-05-27T10:17:26Z
dc.date.issued 2018-05-07
dc.identifier.uri http://hdl.handle.net/20.500.11948/2743
dc.description.abstract This paper focuses on two common applications of image processing done with the help of neural network. At first, it gives a solution for detection of counterfeit bank notes using Artificial Neural Network with the structured image dataset of the corresponding bank notes provided by the UCI Machine Learning Repository. In the second part, the emphasis is on solving the unstructured image classification problem through Convolutional Neural Network and using the famous Kaggle dataset. Both problem include a common Artificial Neural Network architecture. However, in the second problem, on top of Artificial Neural Network, two convolutional layers are added. Two classifications discussed here are non-linear in nature and they have some inherent differences. This paper also discuss the common pitfalls and possible improvement techniques in the future implementation of this strategy along with a detailed discussion. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Authentication of bank notes en_US
dc.subject Authentication of image processing en_US
dc.subject Authentication of bank notes and image processing through Artificial en_US
dc.subject Image processing en_US
dc.title Authentication of bank notes and image processing through Artificial and Convolutional Neural Network en_US
dc.type Thesis en_US


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