Static-gesture word recognition in Bangla sign language using convolutional neural network

EMG-based wrist gesture recognition using a convolutional neural network

Background: Deep learning has revolutionized artificial intelligence and has transformed many fields. It allows processing high-dimensional data (such as signals or images) without the need for feature engineering. The aim of this research is to develop a deep learning-based system to decode motor intent from electromyogram (EMG) signals. Methods: A myoelectric system based on convolutional ne...

Neural Network Based Static Sign Gesture Recognition System

Sign language is natural media of communication for the hearing and speech impaired all over the world This paper presents vision based static sign gesture recognition system using neural network. This system enables deaf people to interact easily and efficiently with normal people. The system firstly convert images of static gestures of American Sign Language into Lab color space where L for l...

Hand Gesture Recognition using Sign Language

Sign Language is mostly used by deaf and dumb people. In order to improve the man machine interaction, sign language can be used as a way for communicating with machines. Most of the applications which enable sign language processing are using data gloves and other devices for interacting with computers. This restricts the freedom of users. So to avoid this, this system we capture live video st...

Automatic Recognition of Bangla Sign Language

Static hand gesture recognition using neural networks

This paper presents a novel technique for hand gesture recognition through human–computer interaction based on shape analysis. The main objective of this effort is to explore the utility of a neural network-based approach to the recognition of the hand gestures. A unique multi-layer perception of neural network is built for classification by using backpropagation learning algorithm. The goal of...