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Machine Learning-Based Fast Banknote Serial Number Recognition Using Knowledge Distillation and Bayesian Optimization
- Title
- Machine Learning-Based Fast Banknote Serial Number Recognition Using Knowledge Distillation and Bayesian Optimization
- Authors
- Choi, Eunjeong; Chae, Somi; Kim, Jeongtae
- Ewha Authors
- 김정태
- SCOPUS Author ID
- 김정태
- Issue Date
- 2019
- Journal Title
- SENSORS
- ISSN
- 1424-8220
- Citation
- SENSORS vol. 19, no. 19
- Keywords
- banknote serial number recognition; deep learning; knowledge distillation
- Publisher
- MDPI
- Indexed
- SCIE; SCOPUS
- Document Type
- Article
- Abstract
- 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.
- DOI
- 10.3390/s19194218
- Appears in Collections:
- 공과대학 > 전자전기공학전공 > Journal papers
- Files in This Item:
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Machine Learning-Based Fast Banknote.pdf(1.98 MB)
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