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HAND GESTURE RECOGNITION USING CONVOLUTION NEURAL NETWORKS

Project Code CB1020
Application Type DESKTOP APP
Tech/Programming PYTHON

API:
NONE
Web Framework:
NOT APPLICABLE
IDE:
VS CODE
Database:
NOT REQUIRED
DFD Diagram:
Not Available
Videos:
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E-R Diagram:
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UML Diagrams:
Available
Final PPT:
Available
SRS:
Available

Description

Hand gestures are the most common forms of communication and have great importance in our world. They can help in building safe and comfortable user interfaces for a multitude of applications. Various computer vision algorithms have employed color and depth camera for hand gesture recognition, but robust classification of gestures from different subjects is still challenging. I propose an algorithm for real-time hand gesture recognition using convolutional neural networks (CNNs). The proposed CNN achieves an average accuracy of 98.76% on the dataset comprising of 9 hand gestures and 500 images for each gesture.

Note

Project with Source Code, Documentation and PPT

1st Review PPT:
Available
2nd Review PPT:
Available
3rd Review PPT:
Available
Architecture Diagram:
Available

Literature Survey:
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Test Cases:
Not Available
Data Dictionary:
Not Available
Future Enhancement:
Available

SRS:
Available
All Modules:
Available
Documentation:
Available
Screen Shots:
Available

How to Install Softwares :Not Available
How to Execute Project :Not Available
Project Explanation Video :Not Available

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