Real time sign language detection system using deep learning techniques

Authors

  • N. Padmaja
  • B.Nikhil Sai Raja
  • B.Pavan Kumar

DOI:

https://doi.org/10.47750/pnr.2022.13.S01.126

Keywords:

deaf; hearing problem; communication; normal people; survey; vision based; deep learning; Faster RCNN; ResNet50.

Abstract

Humans require communication in order to survive. It is a fundamental and effective method for communicating thoughts, feelings, and points of view. A greater number of babies are being born with hearing abnormalities, which puts them at a communication disadvantage with the rest of the world, according to data on physically challenged children during the last decade. People who are deaf or hard of hearing typically use sign languages to communicate. Hand gestures are used by Deaf or Mute persons to communicate; as a result, non-Deaf people have a hard time understanding their messages. Systems that can detect different signs and provide information to common people are thus necessary. To address this issue, we have developed an automated sign language detection system using deep learning, which helps deaf/mute people can communicate with normal people.

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Published

2022-09-26

Issue

Section

Articles

How to Cite

Real time sign language detection system using deep learning techniques. (2022). Journal of Pharmaceutical Negative Results, 1052-1059. https://doi.org/10.47750/pnr.2022.13.S01.126