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American Sign Language Detection with CNN

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Detail Description

Abstract

American Sign Language (ASL) Detection is a deep learning-based system that recognizes hand gestures representing letters and words using a Convolutional Neural Network (CNN). By processing real-time images or video input, the system translates sign language into text, improving communication accessibility for the deaf and hard-of-hearing community.


Existing System

  1. Manual interpretation of sign language
  2. Sensor-based gloves for gesture detection
  3. Basic image processing techniques


Proposed System

  1. CNN model for hand gesture recognition
  2. Real-time detection using webcam input
  3. Converts gestures into text output


Software Requirements

  1. Python
  2. TensorFlow / Keras or PyTorch
  3. OpenCV
  4. NumPy, Pandas
  5. Matplotlib
  6. Jupyter Notebook / VS Code


Hardware Requirements

Minimum:

  1. Intel i3, 4GB RAM, Webcam

Recommended:

  1. Intel i5/i7, 8GB+ RAM, HD Webcam, GPU (optional)





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American Sign Language Detection with CNN
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