Sign Language recognition using Tensorflow-Keras

Registration ID: IJNRD_191325

Published ID: IJNRD2305018

DOI: Click Here to Get

Sowmiya S.R , Sathiyavani E , Soundarya M , Kaushica K , Brindha P

Vision-Based Approach, Communication, TensorFlow, Keras, CNN, Gestures.

Communication through signing is a fundamental instrument for individuals who haven't gotten the endowment of talking and tuning in. Ordinary individuals for the most part do not learn gesture-based communication to speak with hearing/discourse-hindered individuals. Likewise, every time these diversely abled individuals can't keep a human interpreter with them. This makes a correspondence hole among typical and hearing/discourse-disabled individuals. So, to overcome this issue, different gesture-based communication interpreters and acknowledgment methods have been created which are talked about in this paper. we got the inspiration to do this project from persons who are facing the difficulties of hearing impairment. So, we decided to derive a solution for this problem. In this paper, we propose a TensorFlow-Keras which is the model of CNN to manage this issue. TensorFlow is the most broadly utilized system because its adaptability additionally gives great comfort to troubleshooting TensorFlow applications. It very well may be considered a decent programming framework where tasks are sent as charts. Here, we used the Convolutional Neural Network for processing the images of the gestures. The Experimental results of our projects bring about our task show of agreeable recognizable proof of motions under different increase strategies. Besides, the proposed approach just requires a tiny number of preparing ages to accomplish 96.29 percent exactness.

Published Paper   E-Certificate

Sowmiya S.R, Sathiyavani E, Soundarya M, Kaushica K, & Brindha P (May-2023). Sign Language recognition using Tensorflow-Keras. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), a133-a139. https://ijnrd.org/papers/IJNRD2305018.pdf

Volume 8 Issue 5, May-2023

Pages : a133-a139

Paper Reg. ID: IJNRD_191325

Published Paper Id: IJNRD2305018

Downloads: 000121984

Research Area: Science & Technology

Country: Perambalur, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305018.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305018

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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