Transfer Learning Utilization for Banknote Recognition: a Comparative Study Based on Bosnian Currency

Abstract

Transfer learning introduces the ability to perform deep learning models over a small set of data. This paper investigates the utilization of three fine-tuned Convolutional Neural Networks (CNNs), namely, Alexnet, Googlenet, and Vgg16. Alexnet and Googlenet consider as the state-of-the-art models in deep learning, while Vgg16 preference due to its depth. Each model was fine-tuned, trained, and tested over a dataset contains Bosnian Banknotes (BAM). The dataset covers 11 classes where 10 images were collected through mobile phone camera for each class. Alexnet showed a better performance in terms of completing the training while Vgg16 showed better performance in terms of accuracy as it achieved 100% compared to 95.24% for Alexnet. Googlenet showed less efficient performance by achieving 88.65%.