A Graph Neural Network based Fake Currency Recognition Approach

In general, fake currencies are being circulated around, for collapsing the country’s economy. It is achieved by spreading the money to foreign tourist people and vision-impaired people. This proposed work aims to assist such people on detecting the genuineness of the currencies given to them. The work is designed using a customized Graph Neural Network (GNN) -based approach for estimations, and its performance is compared to the traditional Convolution Neural Network, K-Nearest Neighbor, and VGG16 network. This experimental study has been performed utilizing an openly available dataset called Indian currency notes from Kaggle website. The outcome of the study indicates that the suggested GNN model performs better than the existing approaches.