Earticle

초록

영어

Scene Text Detection and Recognition is a problem of reading letters from everyday landscape images. Recently, STR research using deep learning models has been actively conducted for various applications. However, STR still has many challenges to overcome due to the complexity in image contents, which is much more challenging compared to recognizing letters in paper documents. In addition, the STR performance appears good for foreign characters such as English or Chinese, but poor for Korean. In this paper, we develop a model suitable for the Korean environment through the real world Korean scene text dataset. We measure the performance of various configurations of networks to find suitable network structure.

목차

Abstract
I. INTRODUCTION
II. MATERIALS AND METHODS
A. Proposed overall framework
B. Dataset for training and testing the model
III. EXPERIMENTS AND RESULT
A. Experimental results
B. Improve performance when changing each network
C. Inference Image
IV. CONCLUSIONS AND FUTURE WORK
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• JuHoon Park [ dept. of Computer Science and Engineering Sogang University ]
• Byeonggeon Park [ dept. of Computer Science and Engineering Sogang University ]
• Unsang Park [ dept. of Computer Science and Engineering Sogang University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004