Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters

Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters

According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning mediums for those languages. Thus this paper proposes an interact...

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Bibliographic Details
Main Author: Kanchon Kanti, Podder (author)
Other Authors: Emdad Khan, Ludmila (author), Chakma, Jyoti (author), Chowdhury, Muhammad E.H. (author), Dutta, Proma (author), Salam, Khan Md Anwarus (author), Khandakar, Amith (author), Ayari, Mohamed Arselene (author), Bhawmick, Bikash Kumar (author), Islam, S M Arafin (author), Kiranyaz, Serkan (author)
Format: article
Published: 2023
Subjects:
Chakma language
Handwritten character recognition
Deep learning
Self-ONN
Online Access:http://dx.doi.org/10.1016/j.eij.2023.100413
https://www.sciencedirect.com/science/article/pii/S1110866523000695
http://hdl.handle.net/10576/54042
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http://dx.doi.org/10.1016/j.eij.2023.100413
https://www.sciencedirect.com/science/article/pii/S1110866523000695
http://hdl.handle.net/10576/54042

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