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Supervised and Unsupervised Data Engineering for Multimedia Data
book

Supervised and Unsupervised Data Engineering for Multimedia Data

by Suman Kumar Swarnkar, J. P. Patra, Sapna Singh Kshatri, Yogesh Kumar Rathore, Tien Anh Tran
May 2024
Beginner to intermediate content levelBeginner to intermediate
336 pages
8h 29m
English
Wiley-Scrivener
Content preview from Supervised and Unsupervised Data Engineering for Multimedia Data

1SLRRT: Sign Language Recognition in Real Time

Monika Lamba1* and Geetika Munjal2

1Department of Computer Science and Engineering (CSE), The NorthCap University, Gurugram, India

2Amity School of Engineering and Technology, Amity University, Noida, Uttar Pradesh, India

Abstract

An application called Sign Language Recognition (SLR) can recognise a variety of non-identical letter movements and translate them into text. In the area of science and technology, this application is extremely significant. It can be used in a variety of machine learning-based applications, including virtual reality. The purpose of the chapter is to develop a convolutional neural network that will recognise the signs captured or focused from the video capture and in turn provide us with correct or accurate output based on text and to improve the accuracy of the real-time sign language recognition via scanning and detecting that would aid other physically challenged individuals. For all individuals who want assistance in communicating with the rest of society, it offers an offline application. In order to produce quick, precise results and to ensure that the material isn’t lost during the evaluation process, it tries to evaluate gestures more efficiently. Real-time sign language recognition involves first identifying images from a video feed that has been acquired using a machine learning model, then identifying edges and vertices, and then determining the desired result using a convolutional neural network. ...

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Publisher Resources

ISBN: 9781119786344Purchase Link