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Learning vector quantization algorithm as classifier for arabic handwritten characters recognition.
| Content Provider | CiteSeerX |
|---|---|
| Author | Ali, Mohamed A. Jumari, Kasmiran Bin Samad, Salina Abd |
| Abstract | Abstract:- In this module, Learning Vector Quantization LVQ neural network is first time introduced as a classifier for Arabic handwriting. Classification has been performed in two different strategies, in first strategy, we use one classifier for all 53 Arabic Character Basic Shapes CBSs in training and testing phases, in second strategy we use three classifiers and three subsets of 53 Arabic CBSs, the three subsets of Arabic CBSs are; ascending CBSs, descending CBSs and embedded CBSs. Three training algorithms; OLVQ1, LVQ2 and LVQ3 were examined and OLVQ1 found as the best learning algorithm. Key-Words:- Classification, Neural Network, Arabic handwritten recognition, Character Recognition 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Vector Quantization Algorithm Arabic Handwritten Character Recognition Arabic Cbss Different Strategy Arabic Character Basic Shape Cbss Learning Algorithm Testing Phase Neural Network First Time First Strategy Second Strategy Character Recognition Arabic Handwriting |
| Content Type | Text |
