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논문 기본 정보

자료유형
학술저널
저자정보
Aaron Daniel Snowberger (Hanbat National University) Choong Ho Lee (Hanbat National University)
저널정보
한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.21 No.2
발행연도
2023.6
수록면
167 - 173 (7page)

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초록· 키워드

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Hangul is unique compared to other Asian languages because of its simple letter forms that combine to create syllabic shapes. There are 24 basic letters that can be combined to form 27 additional complex letters. This produces 51 graphemes. Hangul optical character recognition has been a research topic for some time; however, handwritten Hangul recognition continues to be challenging owing to the various writing styles, slants, and cursive-like nature of the handwriting. In this study, a dataset containing thousands of samples of 51 Hangul graphemes was gathered from 110 freshmen university students to create a robust dataset with high variance for training an artificial neural network. The collected dataset included 2200 samples for each consonant grapheme and 1100 samples for each vowel grapheme. The dataset was normalized to the MNIST digits dataset, trained in three neural networks, and the obtained results were compared.

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Abstract
I. INTRODUCTION
II. RELATED WORK
III. SYSTEM MODEL AND METHODS
IV. RESULTS
V. DISCUSSION AND CONCLUSIONS
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