Currency Detection and Recognition Based on Deep Learning

Abstract

In recent years, deep learning has become the most popular research direction. It mainly trains the dataset through neural networks. There are many different models that can be used in this research project. Throughout these models, accuracy of currency recognition can be improved. Obviously, such research methods are in line with our expectations. In this paper, we mainly use Single Shot MultiBox Detector (SSD) model based on deep learning as the framework, employ Convolutional Neural Network (CNN) model to extract the features of paper currency, so that we can more accurately recognize the denomination of the currency, both front and back. Our main contribution is through using CNN and SSD, the average accuracy of currency recognition is up to 96.6%.