A language model using variable length tokens for open-vocabulary Hangul text recognition

被引：1

作者：

Ryu, SH ^{[1
]}

Kim, JH ^{[1
]}

机构：

[1] Korea Adv Inst Sci & Technol, Div Comp Sci 373 1, Taejon 305701, South Korea

来源：

PATTERN RECOGNITION | 2004年 / 37卷 / 07期

关键词：

language model; character recognition; hangul recognition; open-vocabulary; word recognition;

D O I：

10.1016/j.patcog.2003.12.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a novel language model for Hangul text recognition. Without relying on prior linguistic knowledge in training, the proposed model learns variable length Hangul character sequences, which comprise the elementary tokens of Korean language, and their probabilities from statistics of a raw text corpus. Experiments in handwritten Hangul recognition shows that the proposed language model is effective in postprocessing of recognition results. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

引用

页码：1549 / 1552

页数：4

共 50 条

[41] Language Embedded 3D Gaussians for Open-Vocabulary Scene Understanding
Shi, Jin-Chuan
Wang, Miao
Duan, Hao-Bin
Guan, Shao-Hua
2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2024, 2024, : 5333 - 5343
[42] Learning the lexicon from raw texts for open-vocabulary Korean word recognition
Ryu, S
Kim, JH
SEVENTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS, 2003, : 202 - 206
[43] Active Open-Vocabulary Recognition: Let Intelligent Moving Mitigate CLIP Limitations
Fan, Lei
Zhou, Jianxiong
Xing, Xiaoying
Wu, Ying
2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2024, : 16394 - 16403
[44] Closed- and Open-Vocabulary Approaches to Text Analysis: A Review, Quantitative Comparison, and Recommendations
Eichstaedt, Johannes C.
Kern, Margaret L.
Yaden, David B.
Schwartz, H. A.
Giorgi, Salvatore
Park, Gregory
Hagan, Courtney A.
Tobolsky, Victoria A.
Smith, Laura K.
Buffone, Anneke
Iwry, Jonathan
Seligman, Martin E. P.
Ungar, Lyle H.
PSYCHOLOGICAL METHODS, 2021, 26 (04) : 398 - 427
[45] EdaDet: Open-Vocabulary Object Detection Using Early Dense Alignment
Shi, Cheng
Yang, Sibei
2023 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2023), 2023, : 15678 - 15688
[46] OPEN-VOCABULARY SKELETON ACTION RECOGNITION WITH DIFFUSION GRAPH CONVOLUTIONAL NETWORK AND PRE-TRAINED VISION-LANGUAGE MODELS
Wei, Chao
Deng, Zhidong
2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, ICASSP 2024, 2024, : 3195 - 3199
[47] GaussianGrasper: 3D Language Gaussian Splatting for Open-Vocabulary Robotic Grasping
Zheng, Yuhang
Chen, Xiangyu
Zheng, Yupeng
Gu, Songen
Yang, Runyi
Jin, Bu
Li, Pengfei
Zhong, Chengliang
Wang, Zengmao
Liu, Lina
Yang, Chao
Wang, Dawei
Chen, Zhen
Long, Xiaoxiao
Wang, Meiqing
IEEE ROBOTICS AND AUTOMATION LETTERS, 2024, 9 (09): : 7827 - 7834
[48] CTC-aligned Audio-Text Embedding for Streaming Open-vocabulary Keyword Spotting
Jin, Sichen
Jung, Youngmoon
Lee, Seungjin
Roh, Jaeyoung
Han, Changwoo
Cho, Hoonyoung
INTERSPEECH 2024, 2024, : 332 - 336
[49] PLA: Language-Driven Open-Vocabulary 3D Scene Understanding
Ding, Runyu
Yang, Jihan
Xue, Chuhui
Zhang, Wenqing
Bai, Song
Qi, Xiaojuan
2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR, 2023, : 7010 - 7019
[50] Open-Vocabulary 3D Semantic Segmentation with Text-to-Image Diffusion Models
Zhu, Xiaoyu
Zhou, Hao
Xing, Pengfei
Zhao, Long
Xu, Hao
Liang, Junwei
Hauptmann, Alexander
Liu, Ting
Gallagher, Andrew
COMPUTER VISION - ECCV 2024, PT XXIX, 2025, 15087 : 357 - 375

← 1 2 3 4 5 →