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Bank Note Detection Using Deep Learning Techniques

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dc.contributor.author Roy, Sojib
dc.contributor.author Satu, Kh. Munsura Akter
dc.date.accessioned 2023-05-03T04:46:23Z
dc.date.available 2023-05-03T04:46:23Z
dc.date.issued 23-02-18
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/10293
dc.description.abstract This report presents a Bangladeshi Banknote detection system using a Deep Convolutional Neural Network. This project is usually designed for people who do not recognize or cannot see the Bangladeshi banknotes. Visually impaired humans face trouble in figuring out and spotting the unique types of banknotes due to a few reasons. Many projects like this have been followed before this project was completed. Some of the works of others are also mentioned in this paper. The detection system is also capable of identifying the Bangladeshi Banknotes that are rumpled, decrepit, or may be worn. The detection system consists of image preprocessing, image evaluation, and image recognition. In this project, 3000 images have been used. There are 50 taka, 100 taka, 200 taka, 500 taka, 1000 taka. This project has been completed using CNN, Vgg16, Transfer learning, and transfer learning-based improved CNN model. We get Better accuracy from improve CNN. We get medium accuracy form Deep CNN and we get low accuracy from VGG16 and transfer learning. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Neural networks en_US
dc.subject Detection system en_US
dc.title Bank Note Detection Using Deep Learning Techniques en_US
dc.type Other en_US


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