Automated recognition of Myanmar sign language using deep learning module

Author:

Kyaw Nwe NiORCID,Mitra Pabitra,Sinha G. R.

Publisher

Springer Science and Business Media LLC

Reference16 articles.

1. Camgöz NC, Kollerq O, Hadfield S, Bowden R (2020) Sign language transformers: joint end-to-end sign language recognition and translation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, Seattle, WA, USA, 14–19 June 2020. pp 10023–10033

2. Aung NH, Thu YK, Maung SS, Moe SZ, New HM (2020) Transfer learning based Myanmar sign language recognition for Myanmar consonants. J Intell Inf Smart Technol 4:35–44

3. Swe YY (2009) Myanmar sign language basic conversation book, 1st edn. Department of Social Welfare, Ministry of Social Welfare, Relief and Resettlement, Department of Social Welfare, Japan International Cooperation Agency, Tokyo

4. Myint STY, Sinha GR (2019) Disambiguation using joint entropy in part of speech of written Myanmar text. Int j inf tecnol 11:667–675. https://doi.org/10.1007/s41870-019-00336-4

5. Fang B, Co J, Zhang M (2018) DeepASL: enabling ubiquitous and non-intrusive word and sentence-level sign language translation. In: Proceedings of the 15th ACM conference on embedded network sensor systems, pp 1–13. https://doi.org/10.1145/3131672.3131693

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