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Achieving high recognition reliability using decision trees and AdaBoost

  • Xiang Jianying*
  • , Tu Xiao
  • , Lu Yue
  • , Patrick S.P. Wang
  • *此作品的通讯作者
  • East China Normal University
  • Northeastern University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Recognition rate is traditionally used as the main criterion for evaluating the performance of a recognition system. High recognition reliability with low misclassification rate is also a must for many applications. To handle the variability of the writing style of different individuals, this paper employs decision trees and WRB AdaBoost to design a classifier with high recognition reliability for recognizing Bangla handwritten numerals. Experiments on the numeral images obtained from real Bangladesh envelopes show that the proposed recognition method is capable of achieving high recognition reliability with acceptable recognition rate.

源语言英语
主期刊名Document Recognition and Retrieval XV
DOI
出版状态已出版 - 2008
活动Document Recognition and Retrieval XV - San Jose, CA, 美国
期限: 29 1月 200831 1月 2008

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
6815
ISSN(印刷版)0277-786X

会议

会议Document Recognition and Retrieval XV
国家/地区美国
San Jose, CA
时期29/01/0831/01/08

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