A Study on A Recognition Algorithm of Handwritten Japanese DocumentUsing Syntax Self-Organization Model With Data Mining
Project/Area Number |
22500170
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Perception information processing/Intelligent robotics
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Research Institution | Tokyo National College of Technology |
Principal Investigator |
SUZUKI Masato 東京工業高等専門学校, 情報工学科, 教授 (50290721)
|
Co-Investigator(Kenkyū-buntansha) |
MATSUMOTO Akiyo 東北学院大学, 教養学部, 講師 (40413752)
|
Co-Investigator(Renkei-kenkyūsha) |
KITAKOSHI Daisuke 東京工業高等専門学校, 情報工学科, 准教授 (50378238)
MATSUMOTO Akiyo 東北学院大学, 教養学部, 講師 (40413752)
|
Project Period (FY) |
2010 – 2012
|
Project Status |
Completed (Fiscal Year 2012)
|
Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
Keywords | パターン認識 / 機械学習 / データマイニング / 自然言語処理 / パタン認識 / 手書き文書自動認識 / 手書き文章自動認識 |
Research Abstract |
It is difficult to realize high recognition accuracy in Japanese handwritten document recognition, since a writer's peculiarity appeared strongly in type and the text itself don’t agree in Japanese syntax. In this research, we propose the self-organization model of Japanese syntax using natural language processing a data mining, and the self-organization model of learning patterns of chinese character recognition. As a result, the recognition accuracy of Japanese handwritten document is improved compared with the conventional method.
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Report
(4 results)
Research Products
(107 results)