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Handwritten Grapheme Classification in Bengali Language Using MobileNet
  • Taif Al Musabe
Taif Al Musabe
University of Manitoba

Corresponding Author:[email protected]

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Abstract

Bengali is one of the world's most widely spoken languages. Due to its 49 alphabets, this language poses a number of challenges in Optical Character Recognition (OCR). Identifying handwritten graphemes is one of them. Now, the grapheme root, vowel diacritic, and consonant diacritic are the three components of the Bengali grapheme. Therefore, we address this topic by treating it as a multi-label classification problem. In this study, we used the MobileNet architecture. Also, the model we designed performs really well.
27 Dec 2023Submitted to TechRxiv
02 Jan 2024Published in TechRxiv