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About Sign Language Recognition Using Deep Learning and Computer Vision
This document summarizes a research paper on sign language recognition using deep learning and computer vision. The authors developed a custom convolutional neural network (CNN) model with 11 layers to recognize American Sign Language gestures from video frames. The model was trained on the MNIST dataset containing images of hand gestures for the ASL alphabet. The CNN architecture included convolutional, max pooling, dense, and dropout layers. The goal is to enable communication between deaf/mute people and those without sign language skills by translating signs to text in real-time.
Detailed Information
| Author: | ['GABRIEL NICODEMO ESPINOZA HUAM�N'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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