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New Index
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Item
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Handwriting Digit Recognition Using Genetic Algorithm
http://hdl.handle.net/20.500.12678/0000003436
http://hdl.handle.net/20.500.12678/00000034364c6e954f-bd2e-40c7-9a8b-6cc76e199529
ef400f7f-a247-4019-96ac-7665a01adacf
Name / File | License | Actions |
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Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Handwriting Digit Recognition Using Genetic Algorithm | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Myint, Nan San San | ||||||
Thwin, Khin Lay | ||||||
Description | ||||||
Handwriting digit recognition is a challenging problem researchers had been research into this area for so long especially in the recent years. In this paper, this system used to recognize the handwritten digits of Kayin language. Genetic algorithm gives an effective Kayin digit to determine the optimal weight parameters that are multiplied by the network outputs. Neural networks have been recognized as a powerful tool for pattern recognition problems. This system checked the digit that is written manually by users and used Genetic Algorithm to produce the output result in order to recognize the Kayin digit. Then, it produces the nearly similar Kayin digit pattern. | ||||||
Keywords | ||||||
Handwriting digit recognition, Artificial Neural Network, Genetic Algorithm | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/1186 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |