Offline Printed Urdu Nastaleeq Script Recognition with Bidirectional LSTM Networks

@article{UlHasan2013OfflinePU,
  title={Offline Printed Urdu Nastaleeq Script Recognition with Bidirectional LSTM Networks},
  author={Adnan Ul-Hasan and Saad Bin Ahmed and Sheikh Faisal Rashid and Faisal Shafait and Thomas M. Breuel},
  journal={2013 12th International Conference on Document Analysis and Recognition},
  year={2013},
  pages={1061-1065}
}
Recurrent neural networks (RNN) have been successfully applied for recognition of cursive handwritten documents, both in English and Arabic scripts. Ability of RNNs to model context in sequence data like speech and text makes them a suitable candidate to develop OCR systems for printed Nabataean scripts (including Nastaleeq for which no OCR system is available to date). In this work, we have presented the results of applying RNN to printed Urdu text in Nastaleeq script. Bidirectional Long Short… CONTINUE READING
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