Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/524
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dc.contributor.authorSarveswaran, K.
dc.contributor.authorRatnaweera, D.A.A.C.
dc.date.accessioned2014-07-11T08:01:51Z
dc.date.accessioned2022-06-28T04:51:42Z-
dc.date.available2014-07-11T08:01:51Z
dc.date.available2022-06-28T04:51:42Z-
dc.date.issued2007-11
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/524-
dc.description.abstractHandwritten character recognition is playing a vital role in many areas of modern world. Even though considerable research work has been done in handwritten character recognition, comparatively fewer efforts have been made on handwritten Tamil character recognition. This paper proposes an adaptable method for recognizing handwritten Tamil characters. The adaptability is achieved using a type of artificial neural network called Kohonen self organizing maps (KSOM). In addition, a fine-tuning method, that uses global features, is admitted to fine tune the results. A demo for proposed concept is presented here, which is developed for a subset of Tamil alphabet. The demo gives a recognition accuracy of 86%.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.titleAn adaptive technique for handwritten Tamil character recognitionen_US
dc.typeArticleen_US
Appears in Collections:Computer Science

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