DocumentCode
3398193
Title
Bangla Hand Written digit recognition using supervised locally linear embedding algorithm and Support Vector Machine
Author
Ahmed, Saleh ; Islam, Md Rafiqul ; Azam, Md Shafiul
Author_Institution
Dept. of CSE, Leading Univ., Sylhet, Bangladesh
fYear
2009
fDate
21-23 Dec. 2009
Firstpage
390
Lastpage
393
Abstract
This paper presents Bangla numeral character recognition system using supervised locally linear embedding algorithm and support vector machine (SVM). The locally linear embedding (LLE) algorithm is an unsupervised technique proposed for nonlinear dimensionality reduction. In this paper, we describe its supervised variant (SLLE). Where class membership information is used to map overlapping high dimensional data into disjoint clusters in the embedded space. we combined it with support vector machine (SVM) for classifying handwritten digits from the on-line handwritten Bangla numeral database.
Keywords
handwritten character recognition; image classification; natural language processing; support vector machines; unsupervised learning; Bangla hand written digit recognition; Bangla numeral character recognition system; class membership information; handwritten digit classification; nonlinear dimensionality reduction; online handwritten Bangla numeral database; supervised locally linear embedding algorithm; support vector machine; unsupervised technique; Character recognition; Clustering algorithms; Embedded computing; Handwriting recognition; Image databases; Image recognition; Information technology; Nearest neighbor searches; Support vector machine classification; Support vector machines; Bangla Handwritten; Digit Recognition; LLE; SLLE; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Computers and Information Technology, 2009. ICCIT '09. 12th International Conference on
Conference_Location
Dhaka
Print_ISBN
978-1-4244-6281-0
Type
conf
DOI
10.1109/ICCIT.2009.5407269
Filename
5407269
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