IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

Comparing Classification Algorithms on Sign Language Recognition

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Basel A. Dabwan, Mukti E. Jadhav , Prachi Janrao

Abstract

This work is proposed to shows the results various classifier techniques, For the most part of the Deep Learning and Machine Learning-based classifiers were used to distinctive the different gesture languages and this study is proposed to present the best classifier model to Characteristically sign language recognition (SLR), it is essentially utilized as a middle between normal individuals and individuals with inabilities We concentrate mainly on American sign language recognition techniques. Various classifiers like CNN, SVM, KNN, were development to the SLR system. Every classifier shows accuracy of recognition; we noticed the classifiers of deep learning executed the best recognition result as differentiated to different kinds of classifiers.

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