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Balinese character recognition using bidirectional LSTM classifier

conference contribution
posted on 2016-01-01, 00:00 authored by S B Ahmed, S Naz, Imran RazzakImran Razzak, T M Breuel
© Springer International Publishing Switzerland 2016. The character recognition of cursive scripts always be provocative. The inherent challenges exists in cursive scripts captured researcher’s interest to crop up the issues that surface in building a reliable OCR. There exists many ancient languages that require state of the art techniques to be applied on them. Every such language has its own inherent complex structure. We proposed Balinese character recognition system by Recurrent Neural Network (RNN) approach, so that their characteristics may get substantial attention from research community. The Balinese has Brahmic Indic ancestor having cursive writing style nearest to Devangri, Sinhala and Tamil. We employed BLSTM networks on Balinese character recognition.

History

Event

Machine Learning and Signal Processing. International Conference (2015 : Ho Chi Minh City, Vietnam)

Volume

387

Pagination

201 - 211

Publisher

Springer

Location

Ho Chi Minh City, Vietnam

Place of publication

Cham, Switzerland

Start date

2015-12-15

End date

2015-12-17

ISSN

1876-1100

eISSN

1876-1119

ISBN-13

9783319322124

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

P Soh, W Woo, H Sulaiman, M Othman, M Saat

Title of proceedings

MALSIP 2015 : Advances in Machine Learning and Signal Processing

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