| Autor: |
Prasad, M., P. B. V., Raja Rao, Murty, Ch. S. V. V. S. N., Sushma, N., Babu, V. Rajesh, Naidu, Vegi Narasimham, Lakshmi, K. Ajita, Sree, P. Kiran |
| Předmět: |
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| Zdroj: |
Grenze International Journal of Engineering & Technology (GIJET); Jun2024, Vol. 10 Issue 2, Part 2, p459-465, 7p |
| Abstrakt: |
Tangible currency is an integral aspect of daily lives, and discerning its denomination can pose a considerable challenge. In the digital age, the field of computing unfolds vast possibilities for groundbreaking achievements. The exploration of object detection from images has emerged as a captivating research avenue in recent years, leveraging various deep learning techniques. As part of the training and testing datasets, this framework is designed to recognize and identify currency denominations based on trained images of Indian currency in seven different orientations. Employing a Convolutional Neural Networks (CNN), model ensures the precise extraction of features, as evidenced by experimental results showcasing a commendable 98.32% training accuracy and 83.48% validation accuracy. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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