Scholarlink

The system presented in this project aims to break down communication barriers for visually impaired individuals by translating written Braille into both text and audio formats. It leverages advanced machine learning techniques to accurately interpret Braille symbols and convert them into readable text. The system employs convolutional neural networks (CNNs) to improve the precision of Braille recognition. In addition, text-to-speech functionality is integrated to provide audio output, making the system more accessible. This project highlights the power of machine learning in creating inclusive solutions that cater to diverse user needs.

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Echoing the Dots: Braille Recognition Using Convolutional Neural Network

  • 会议论文

  • 发表日期：

    2025年

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  • Jyoti Kanjalkar,
  • Pramod Kanjalkar,
  • Harsh Ukey,
  • Vaibhav Aher,
  • Sujal Dubey,
  • Onkar Kolekar

摘要

The system presented in this project aims to break down communication barriers for visually impaired individuals by translating written Braille into both text and audio formats. It leverages advanced machine learning techniques to accurately interpret Braille symbols and convert them into readable text. The system employs convolutional neural networks (CNNs) to improve the precision of Braille recognition. In addition, text-to-speech functionality is integrated to provide audio output, making the system more accessible. This project highlights the power of machine learning in creating inclusive solutions that cater to diverse user needs.