DocumentCode
2508086
Title
An improved two-layer SOM classifier for handwritten numeral recognition
Author
Lu, Shujing ; Tu, Xiao ; Lu, Yue
Author_Institution
Shanghai Res. Inst. of China Post Group, Shanghai
fYear
2008
fDate
8-11 July 2008
Firstpage
367
Lastpage
371
Abstract
In the past several years, wepsilave been developing a high performance two-layer SOM classifier for handwritten Bangla numeral recognition. We have reported previously the structure and the learning algorithm of the two-layer SOM. In this paper, we fuse the outputs of the second layer SOMs to improve the classification ability, based on confidence coefficient of the SOMs in the second layer. Experimental results on the numeral images obtained from real Bangladesh envelopes have proved the validity of the proposed method.
Keywords
handwritten character recognition; image classification; image fusion; learning (artificial intelligence); natural languages; self-organising feature maps; confidence coefficient; handwritten Bangla numeral recognition; image fusion; learning algorithm; two-layer SOM classifier; Computer science; Error analysis; Fuses; Handwriting recognition; Merging; Neurons; Pattern recognition; Unsupervised learning; Vector quantization; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology, 2008. CIT 2008. 8th IEEE International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4244-2357-6
Electronic_ISBN
978-1-4244-2358-3
Type
conf
DOI
10.1109/CIT.2008.4594703
Filename
4594703
Link To Document