Cross-Age Real-Time Kannada Sign Language Recognition using Curvilinear Geometric Features and CNN-LSTM Models
This study introduces a robust, real-time framework for cross-age Kannada Sign Language recognition that integrates curvilinear geometric feature extraction with a hybrid CNN-LSTM architecture, achieving 94.6% accuracy on a newly curated dataset of 5,000 annotated samples to facilitate effective sign-to-text translation for assistive communication.
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