Forthcoming and Online First Articles

International Journal of Systems, Control and Communications

International Journal of Systems, Control and Communications (IJSCC)

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International Journal of Systems, Control and Communications (One paper in press)

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  • Tamil sign language using relational bilevel aggregation graph convolutional network   Order a copy of this article
    by Shashi Kumar Gowdagere Siddaramaiah, R. Vinoth 
    Abstract: Automatic translation of sign language to text facilitates communication between deaf or mute persons and others, including those who are not comfortable with sign language. In this manuscript, Identification of Tamil sign language utilising relational bilevel aggregation graph convolutional network (IDN-TSL-RBAGCN) is proposed. Initially, the data is collected through Tamil sign language gesture images. Artificial lizard search optimisation algorithm (ALSOA) is employed to enhance the weight parameter of relational bilevel aggregation graph convolutional network classifier (RBAGCN), which precisely classifies the Tamil sign language from the identified pattern. The proposed IDN-TSL-RBAGCN method attains 28.76%, 33.68% and 21.78% higher accuracy when compared with existing methods, like Indian sign language recognition utilising wearable sensors with multiple label categorisation (ISL-MLC), deep learning-dependent sign language recognition system for static signs (SLR-DL), and real-time vernacular sign language recognition utilising media pipe and machine learning (SLR-ML) respectively.
    Keywords: artificial lizard search optimisation algorithm; Tamil sign language; adaptive-noise augmented Kalman filter; multi-objective matched synchrosqueezing chirplet transform.

 

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