Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Sign Detection and Recognition Using CNN and Machine Learning

Sign Detection and Recognition Using CNN and Machine Learning

Jadhav, Varsha
Sonwane, Samradhny
Wanjle, Kirti

Paperback

Technology & Engineering

ISBN10: 365986790X
ISBN13: 9783659867903
Publisher: LAP Lambert Academic Publishing
Published: Nov 12 2024
Pages: 52
Weight: 0.20
Height: 0.12 Width: 6.00 Depth: 9.00
Language: English
Sign language is a primary mode of communication for the deaf and hard-ofhearing community, providing a rich, visual language that enables expression and connection. However, for individuals who do not understand sign language, communication barriers persist. With recent advances in computer vision and deep learning, automated sign language recognition systems offer promising solutions to bridge this gap, enabling real-time translation of hand gestures into text or spoken language. This project focuses on implementing a real-time sign language recognition system using Convolutional Neural Networks (CNNs) to identify static hand gestures representing letters of the English alphabet.

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