Home > Engineering > Computer Engineering > Special Issue > Smart Innovations in Computer Science and Applications > Sign Language Recognition System Using a Convolution Neural Network Model

Sign Language Recognition System Using a Convolution Neural Network Model

Call for Papers

Volume-10 | Issue-5

Last date : 27-Oct-2026

Best International Journal
Open Access | Peer Reviewed | Best International Journal | Indexing & IF | 24*7 Support | Dedicated Qualified Team | Rapid Publication Process | International Editor, Reviewer Board | Attractive User Interface with Easy Navigation

Journal Type : Open Access

First Update : Within 7 Days after submittion

Submit Paper Online

For Author

Research Area


Sign Language Recognition System Using a Convolution Neural Network Model


Arshiya Javed Sheikh



Arshiya Javed Sheikh "Sign Language Recognition System Using a Convolution Neural Network Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.161-171, URL: https://www.ijtsrd.com/papers/ijtsrd101614.pdf

Deaf and hard-of-hearing individuals use sign language to communicate with their peers and others. The process of using computers to recognize the sign language involves recognizing signs through gesture recognition as well as converting signs into text or speech. The signs can be classified as either static or dynamic, with static gesture recognition being easier than dynamic gesture recognition; however, both types of gesture recognition systems are very useful to the human community. This paper describes the methods used to recognize sign language. The different stages of sign language recognition, such as how the data is collected, preprocessed, transformed, and recognized, as well as the results from using these methods, are discussed within this article. Several future research avenues regarding sign language recognition are also presented.

sign language recognition; static gesture recognition; dynamic gesture recognition; gesture analysis; face recognition


IJTSRD101614
Special Issue | Smart Innovations in Computer Science and Applications, March 2026
161-171
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

Thomson Reuters
Google Scholer
Academia.edu

ResearchBib
Scribd.com
archive

PdfSR
issuu
Slideshare

WorldJournalAlerts
Twitter
Linkedin