DocumentCode
1648424
Title
Fast recognition of handwritten digits using pairwise coupling support vector machine
Author
Zeyu, Li ; ShiWei, Tang ; Hao, Wang
Author_Institution
Nat. Lab. on Machine Perception, Peking Univ., Beijing, China
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
878
Lastpage
883
Abstract
In this paper, a hierarchical structure combining a linear classifier based on the Mahalanobis distance and pairwise coupling (PWC) is proposed to effectively tackle multi-class classification problem. By taking the advantage of the distribution information of the dataset, both the recognition rate and speed are all improved. At the same time, the proposed method can estimate the posterior probabilities of a testing pattern more accurately than the classical PWC in multi-class cases. Experimental results on handwritten digit recognition demonstrate the effectiveness and efficiency of our method
Keywords
handwritten character recognition; learning automata; neural nets; optimisation; pattern classification; probability; Mahalanobis distance; handwritten digit recognition; hierarchical structure; linear classifier; multiple class pattern classification; optimization; pairwise coupling; posterior probability; support vector machine; Computer science; Educational institutions; Face recognition; Handwriting recognition; Laboratories; Support vector machine classification; Support vector machines; Testing; Text recognition; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005590
Filename
1005590
Link To Document