Academic Journal
Deep learning-based recognition system for pashto handwritten text: benchmark on PHTI
| العنوان: | Deep learning-based recognition system for pashto handwritten text: benchmark on PHTI |
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| المؤلفون: | Hussain, Ibrar, Ahmad, Riaz, Ullah, Khalil, Muhammad, Siraj, Elhassan, Rasha, Syed, Ikram |
| المساهمون: | King Khalid University Deanship of Scientific Research through the General Research Project under grant number |
| المصدر: | PeerJ Computer Science ; volume 10, page e1925 ; ISSN 2376-5992 |
| بيانات النشر: | PeerJ |
| سنة النشر: | 2024 |
| المجموعة: | PeerJ (E-Journal - via CrossRef) |
| الوصف: | This article introduces a recognition system for handwritten text in the Pashto language, representing the first attempt to establish a baseline system using the Pashto Handwritten Text Imagebase (PHTI) dataset. Initially, the PHTI dataset underwent pre-processed to eliminate unwanted characters, subsequently, the dataset was divided into training 70%, validation 15%, and test sets 15%. The proposed recognition system is based on multi-dimensional long short-term memory (MD-LSTM) networks. A comprehensive empirical analysis was conducted to determine the optimal parameters for the proposed MD-LSTM architecture; Counter experiments were used to evaluate the performance of the proposed system comparing with the state-of-the-art models on the PHTI dataset. The novelty of our proposed model, compared to other state of the art models, lies in its hidden layer size ( i.e ., 10, 20, 80) and its Tanh layer size ( i.e. , 20, 40). The system achieves a Character Error Rate (CER) of 20.77% as a baseline on the test set. The top 20 confusions are reported to check the performance and limitations of the proposed model. The results highlight complications and future perspective of the Pashto language towards the digital transition. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.7717/peerj-cs.1925 |
| الاتاحة: | http://dx.doi.org/10.7717/peerj-cs.1925 https://peerj.com/articles/cs-1925.pdf https://peerj.com/articles/cs-1925.xml https://peerj.com/articles/cs-1925.html |
| Rights: | https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: | edsbas.C1E45B1 |
| قاعدة البيانات: | BASE |
| DOI: | 10.7717/peerj-cs.1925 |
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