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This research paper presents a hybrid deep learning framework for gesture language recognition, combining continuous and isolated sign language recognition using a Spatial-Temporal Network (STNet) and Convolutional Neural Network (CNN). The proposed system achieved an accuracy of 98.46% in isolated sign recognition and a 2.9% improvement in continuous sign language recognition tasks, demonstrating superior performance compared to existing techniques. The advancements in this model enhance real-time translat

Author

ARIN AZCONA BENDEZÚ

Language

EN