DIAGRAPH SIGN LANGUAGE RECOGNITION USING RESIDUAL NETWORK AND SUPPORT VECTOR MACHINE

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  • Create Date November 4, 2023
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DIAGRAPH SIGN LANGUAGE RECOGNITION USING RESIDUAL NETWORK AND SUPPORT VECTOR MACHINE

ABSTRACT

In human life, communication is a way of exchanging information, Humans communicate with one another not only through speech but also through a variety of other means. Sign language translation (SLT) is a critical application for bridging communication barrier between the deaf and the hearing. This paper used Residual Network (ResNet18) as feature extractor and Support Vector Machine (SVM) as the classifier. An accuracy of 79.3% was recorded. The proposed technique can be when implemented can facilitate learning process for hearing-impaired students.

Keywords: Diagraph Sign, Deaf School, ResNet, Sign Recognition

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