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hand-signs

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Real-time sign language recognition with MediaPipe hand/face/pose landmarks and a two-stream (appearance + motion) 1D-CNN + Transformer with motion-gated attention. Trained on 36-class ASL static gestures (val 93.6% / test 89.6%), live Streamlit webcam inference with confidence thresholding, top-3 predictions, and validation sampling.

  • Updated Oct 6, 2026
  • Python

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