Currency Recognition Based on Deep Learning
Yihao Wang · 2023
Currency recognition is a critical task with diverse applications. Recent advancements in deep learning and neural networks have shown significance in improving its accuracy and robustness. This paper presents an approach that utilizes the convolutional neural network (CNN) for accurate and reliable currency recognition. The paper begins with an introduction to the background of the neural network, including its architecture and types, focusing on CNN and its significance in image-processing tasks. Then, the methodology section describes the data collection process, dataset preparation, and the construction of the CNN model. Next, the results and discussion section present the performance of the developed model, discusses the accuracy of the model, and figure out the model’s strengths and areas for improvement. Last, the conclusion summarizes the research findings and evaluates the effectiveness of the proposed neural network-based approach, while also suggesting directions for future research. Overall, the study demonstrates the potential of CNNs in currency recognition and provides insights for further development in this field.