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About Sign Language Recognition Using Deep Learning Through LSTM and CNN
This document summarizes research on using deep learning techniques like LSTM, CNN, and YOLOv5 to recognize sign language. The researchers developed models using these techniques and tested them on datasets of sign language. They found that the YOLOv5 model achieved the highest accuracy of 97% at recognizing sign language, followed by the LSTM and CNN models which achieved 94% and 66.67% accuracy respectively. The document also reviews related work on sign language recognition using deep learning methods like convolutional neural networks and discusses algorithms commonly used in deep learning like convolutional neural networks.
Detailed Information
| Author: | ['Victor'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 5 |
| Language: | English |
| Format: | |
| Price: | FREE |
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