Goutam1511/Sign-Language-Recognition-using-Scikit-Learn-and-CNN
The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).
This project helps people understand individual finger-spelled letters from sign language, converting them into digital text. It takes images of hand gestures as input and identifies the corresponding letter. This tool is designed for anyone needing to interpret finger-spelled sign language, such as educators, communication specialists, or individuals interacting with the deaf community.
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Use this if you need a way to automatically recognize and classify individual finger-spelled letters from images of hand gestures.
Not ideal if you need to interpret full sign language words or sentences, as this focuses only on individual letter recognition.
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Language
Python
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Last pushed
Mar 18, 2018
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