Visual Watermark Identification From the Transparent Window of Currency by Using Deep Learning

Author:

Tong Duo1,Yan Wei Qi1

Affiliation:

1. Auckland University of Technology, New Zealand

Abstract

Banknote identification plays an increasingly important role in financial fields due to the diffusion of automatic bank systems in terms of vending machines. Nowadays, YOLOv5 has become the state-of-the-art detector of visual objects because of its relatively outperformed accuracy with a high speed of computing. In this chapter, the squeeze-excitation (SE) attention module is mingled with the terminal of the backbone in YOLOv5 to further improve visual watermark recognition of paper banknotes. The main contribution of this chapter is that the excellent precision reaches 99.99% by utilizing the novel model YOLOv5+SE.

Publisher

IGI Global

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