Zoning features and 2DLSTM for urdu text-line recognition Naz, Saeeda, Ahmed, Saad Bin, Ahmad, Riaz and Razzak, Muhammad Imran 2016, Zoning features and 2DLSTM for urdu text-line recognition, in KES2016 : 20th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, Elsevier, Amsterdam, The Netherlands, doi: 10.1016/j.procs.2016.08.084. Attached Files Name Description MIMEType Size Downloads Title Zoning features and 2DLSTM for urdu text-line recognition Author(s) Naz, Saeeda Ahmed, Saad Bin Ahmad, Riaz Razzak, Muhammad Imran orcid.org/0000-0002-3930-6600 Conference name Knowledge Based and Intelligent Information and Engineering Systems (20th : 2016 : York, England) Conference location York, England Conference dates 2016/09/05 - 2016/09/07 Title of proceedings KES2016 : 20th International Conference on Knowledge Based and Intelligent Information and Engineering Systems Publication date 2016 Total pages 7 Publisher Elsevier Place of publication Amsterdam, The Netherlands Summary © 2016 The Authors. Published by Elsevier B.V. Recognition of Urdu cursive script is a challenging task due to the implicit complexities associated with it. The performance of a recognition system is immensely dependent on extracted features. There are various features extraction approaches proposed in recent years. Among many, an approach based on zoning features proved to be efficient and popular. Such zoning features represent significant information with low complexity and high speed. In this paper, we used zoning features for the classification of Urdu Nasta'liq text lines, with a combination of 2-Dimensional Long Short Term Memory networks (2DLSTM) as learning classifier. The proposed model is evaluated on publicly available UPTI dataset and character recognition rate of 93.39% is obtained. Notes Published in the journal Procedia Computer Science, vol 96, pp.16-22 ISSN 1877-0509 Language eng DOI 10.1016/j.procs.2016.08.084 Indigenous content off Field of Research 08 Information and Computing Sciences 10 Technology HERDC Research category E1.1 Full written paper - refereed Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30132590 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Wed, 27 Nov 2019, 08:20:52 EST Thu, 28 Nov 2019, 04:00:20 EST Thu, 28 Nov 2019, 05:04:45 EST Mon, 09 Dec 2019, 08:59:53 EST Mon, 09 Dec 2019, 09:06:22 EST Mon, 09 Dec 2019, 09:06:58 EST Sat, 09 Jan 2021, 01:37:24 EST Filtered Full Citation counts:   Cited 17 times in TR Web of Science Cited 19 times in Scopus Search Google Scholar Access Statistics: 115 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Wed, 27 Nov 2019, 08:20:52 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.