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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.
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Event
Machine Learning and Signal Processing. International Conference (2015 : Ho Chi Minh City, Vietnam)Volume
387Pagination
201 - 211Publisher
SpringerLocation
Ho Chi Minh City, VietnamPlace of publication
Cham, SwitzerlandPublisher DOI
Start date
2015-12-15End date
2015-12-17ISSN
1876-1100eISSN
1876-1119ISBN-13
9783319322124Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
P Soh, W Woo, H Sulaiman, M Othman, M SaatTitle of proceedings
MALSIP 2015 : Advances in Machine Learning and Signal ProcessingUsage metrics
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