Machine Learning-Based Fast Banknote Serial Number Recognition Using Knowledge Distillation and Bayesian Optimization

被引:12
作者
Choi, Eunjeong [1 ]
Chae, Somi [1 ]
Kim, Jeongtae [1 ]
机构
[1] Ewha Womans Univ, Dept Elect & Elect Engn, Seoul 03760, South Korea
基金
新加坡国家研究基金会;
关键词
banknote serial number recognition; deep learning; knowledge distillation;
D O I
10.3390/s19194218
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
We investigated a machine-learning-based fast banknote serial number recognition method. Unlike existing methods, the proposed method not only recognizes multi-digit serial numbers simultaneously but also detects the region of interest for the serial number automatically from the input image. Furthermore, the proposed method uses knowledge distillation to compress a cumbersome deep-learning model into a simple model to achieve faster computation. To automatically decide hyperparameters for knowledge distillation, we applied the Bayesian optimization method. In experiments using Japanese Yen, Korean Won, and Euro banknotes, the proposed method showed significant improvement in computation time while maintaining a performance comparable to a sequential region of interest (ROI) detection and classification method.
引用
收藏
页数:18
相关论文
共 38 条
[1]  
Abello J, 2006, DIMACS SER DISCRET M, V70, P1
[2]   Bangla Handwritten Digit Recognition Using Convolutional Neural Network [J].
Rabby, A. K. M. Shahariar Azad ;
Abujar, Sheikh ;
Haque, Sadeka ;
Hossain, Syed Akhter .
EMERGING TECHNOLOGIES IN DATA MINING AND INFORMATION SECURITY, IEMIS 2018, VOL 1, 2019, 755 :111-122
[3]  
[Anonymous], 2017 INT SYST COMP
[4]  
[Anonymous], 2016, P INT C ADV BIG DAT
[5]  
[Anonymous], 2014, INT J COMPUT APPL, DOI DOI 10.5120/18229-9167
[6]  
[Anonymous], P 2006 INT C INF AUT
[7]  
[Anonymous], SENSORS BASEL
[8]  
[Anonymous], 2016, DEEP LEARNING
[9]  
[Anonymous], ADV NEURAL INFORM PR, DOI DOI 10.1109/TPAMI.2016.2577031
[10]  
[Anonymous], 2015, P NIPS DEEP LEARN WO