Fitriawan, Helmy and Ariyanto, Ariyanto and Setiawan, Hendri (2016) Neural Networks for Lampung Characters Handwritten Recognition. In: 2016 International Conference on Computer & Communication Engineering, 26-27 Juli 2016, Kuala Lumpur, Malaysia.
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Abstract
Character recognition technique associates a symbolic identity with the image of a character. Different characters and languages have different structures and features. Lampung character and language are different with any other languages. We have developed Lampung handwritten character recognition using back-propagation neural networks. However since some Lampung characters have similar features, hierarchical network system was performed to optimize the training and recognition algorithm. The experiment results give reasonable results of the recognition rate for the training set. 86.5% of basic characters and more than 97% for characters with tone marks can be recognised.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Teknik (FT) > Prodi Teknik Elektro |
| Depositing User: | Dr Helmy Fitriawan |
| Date Deposited: | 16 Nov 2020 06:06 |
| Last Modified: | 16 Nov 2020 06:06 |
| URI: | http://repository.lppm.unila.ac.id/id/eprint/25461 |
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Neural Networks for Lampung Characters Handwritten Recognition. (deposited 02 Jun 2017 20:46)
- Neural Networks for Lampung Characters Handwritten Recognition. (deposited 16 Nov 2020 06:06) [Currently Displayed]
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