Currency Recognition Based on Deep Feature Selection and Classification. Trinh, H. C., Vo, H. T., Pham, V. H., Nath, B., & Hoang, V. D. In Communications in Computer and Information Science, volume 1178 CCIS, pages 273–281, 2020. ISSN: 18650937![Currency Recognition Based on Deep Feature Selection and Classification [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Advanced technology has played an important role in the circulation of the banknote counterfeit and currency value recognition. This study proposes an approach for the currency recognition based on the fundamental image processing and deep learning for the extraction characteristics and recognition of currency values. The large capacity of traditional techniques was proposed for currency recognition based on infrared spectrometer and chemometrics using special devices. This paper presents a recognition method to detect face values from currency paper and. The proposed method can recognize some kinds of currency values and national currencies. The study investigated and proposed the deep neural network, which reaches appropriate accuracy rate and reduces consumption time. In order to improve accuracy of recognition model, data augmentation techniques are also investigated for training data preprocessing. The experimental results show that the proposed approach is applicable to the practical applications.
@inproceedings{Van_Huy_Pham_70119969,
title = {Currency {Recognition} {Based} on {Deep} {Feature} {Selection} and {Classification}},
volume = {1178 CCIS},
isbn = {9789811533792},
url = {http://doi.org/10.1007/978-981-15-3380-8%5C_24},
doi = {10.1007/978-981-15-3380-8_24},
abstract = {Advanced technology has played an important role in the circulation of the banknote counterfeit and currency value recognition. This study proposes an approach for the currency recognition based on the fundamental image processing and deep learning for the extraction characteristics and recognition of currency values. The large capacity of traditional techniques was proposed for currency recognition based on infrared spectrometer and chemometrics using special devices. This paper presents a recognition method to detect face values from currency paper and. The proposed method can recognize some kinds of currency values and national currencies. The study investigated and proposed the deep neural network, which reaches appropriate accuracy rate and reduces consumption time. In order to improve accuracy of recognition model, data augmentation techniques are also investigated for training data preprocessing. The experimental results show that the proposed approach is applicable to the practical applications.},
booktitle = {Communications in {Computer} and {Information} {Science}},
author = {Trinh, Hung Cuong and Vo, Hoang Thanh and Pham, Van Huy and Nath, Bhagawan and Hoang, Van Dung},
year = {2020},
note = {ISSN: 18650937},
keywords = {Currency recognition, Deep feature extraction, Deep learning},
pages = {273--281},
}
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This paper presents a recognition method to detect face values from currency paper and. The proposed method can recognize some kinds of currency values and national currencies. The study investigated and proposed the deep neural network, which reaches appropriate accuracy rate and reduces consumption time. In order to improve accuracy of recognition model, data augmentation techniques are also investigated for training data preprocessing. 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