APPLYING HUMAN KNOWLEDGE TO IMPROVE MACHINE RECOGNITION OF CONFUSING HANDWRITTEN NUMERALS

被引：5

作者：

NADAL, C ^{[1
]}

SUEN, CY ^{[1
]}

机构：

[1] CONCORDIA UNIV,DEPT COMP SCI,CTR PATTERN RECOGNIT & MACHINE INTELLIGENCE,1455 MAISONNEUVE BLVD,MONTREAL H3G 1M8,QUEBEC,CANADA

来源：

PATTERN RECOGNITION | 1993年 / 26卷 / 03期

关键词：

HANDWRITTEN NUMERAL; RELIABILITY; KNOWLEDGE BASE; HUMAN EXPERTS; AMBIGUITY;

D O I：

10.1016/0031-3203(93)90166-T

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is believed that the decision making process of existing algorithms can be refined by gaining more human knowledge, especially when trying to recognize confusing characters. Therefore, to help improve machine performance on confusing samples, comments collected from an experiment conducted with a group of human experts specialized in unconstrained handwritten numeral recognition are analyzed. Based on this knowledge, a tool is being built which will manage the information and give results of analyses to help distinguish the different confusing styles of writing. These analyses will facilitate the design of new specialized modules aimed at differentiating numerals belonging to the same confusing pair.

引用

页码：381 / 389

页数：9

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