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다중 언어로 학습된 이미지 기반 문자인식 모델의 성능 분석
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- Issue Date
- 2023-06
- Citation
- 대한전자공학회 학술 대회 (하계) 2023, pp.1058-1061
- Publisher
- 대한전자공학회
- Language
- Korean
- Type
- Conference Paper
- Abstract
- As optical character recognition technology is one of the pattern recognition technologies that have been studied for a long time, deep learning-based scene text recognition (STR) has obtained much attention due to the advances in deep learning and the availability of large-scale text image datasets. However, as the previous deep learning-based STR algorithms are trained with a single language (e.g., English or Chinese), it is limited to applying to a real-world environment where multi-languages appear simultaneously. In this paper, we retrain the off-the-shelf STR deep networks with multilanguages (specifically Korean and English) for the purpose of real-world applications such as text understanding for outdoor signs or banners. Then, the text classification performance of the retrained STR models and the effect of multilingual training are analyzed.