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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Sign Language recognition using Tensorflow-Keras |
| Authors Name: | Sowmiya S.R , Sathiyavani E , Soundarya M , Kaushica K , Brindha P |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_191325
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| Published Paper Id: | IJNRD2305018 |
| Published In: | Volume 8 Issue 5, May-2023 |
| DOI: | |
| Abstract: | 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. |
| Keywords: | Vision-Based Approach, Communication, TensorFlow, Keras, CNN, Gestures. |
| Cite Article: | "Sign Language recognition using Tensorflow-Keras", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.a133-a139, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305018.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2305018 Registration ID: 191325 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: a133-a139 Country: Perambalur, Tamil Nadu, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2305018 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2305018 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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