BE Project : Sign Language Recognition using Deep Learning

Published in International Research Journal of Engineering and Technology (IRJET)

Volume: 09 Issue: 11 | Nov 2022

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Abstract

According to the 2011 Census, In India, out of the total population of 121 crores, approximately 2.68 Crore humans are ‘Disabled’ (2.21% of the whole population)). Sign Language serves as a means for these people with special needs to communicate with others, but it is not a simple task. This barrier to communication has been addressed by researchers for years. The goal of this study is to demonstrate the MobileNets model's experimental performance on the TensorFlow platform when training the Sign language. Language Recognition Model, which can drastically reduce the amount of time it takes to learn a new language. Classification of Sign Language motions in terms of time and space Developing a portable solution for a real-time application. The Mobilenet V2 Model was trained for this purpose and an Accuracy of 70% was obtained.

link to the Publication:

https://www.irjet.net/archives/V9/i11/IRJET-V9I1182.pdf

Contributions:

1. Ankita Mallikarjun Dodamani (Myself)
2. Amit Kuveskar
3. Pranali Wadile
4. Prof. Mrs. Brinzel Rodrigues.