American Sign Language (ASL) recognition systems often struggle with accuracy due to similar gestures, poor image quality and inconsistent lighting. To address this, researchers developed a system ...

Overview Hand-Gesture-2-Robot is a cutting-edge solution for integrating gesture recognition with robot control systems. Whether you are exploring the world of vision-language models or working on a ...

How the System Actually Works The process is more sophisticated than it might seem at first glance. Here is what happens behind the scenes: Hand Detection Stage When you make a sign, MediaPipe first ...

A study is the first-of-its-kind to recognize American Sign Language (ASL) alphabet gestures using computer vision. Researchers developed a custom dataset of 29,820 static images of ASL hand ...

This repository contains the implementation of a real-time gesture recognition system using Mediapipe for keypoint extraction and a Bidirectional LSTM neural network for gesture classification. The ...

The approach incorporates a pre-trained VGG-16 architecture for static gesture recognition and a complex deep learning architecture featuring a bidirectional Convolutional Long Short Term Memory ...

Abstract With the advancement of technology and the increase in user demands, gesture recognition played a pivotal role in the field of human-computer interaction. Among various sensing devices, ...

This paper proposes a Jordan recurrent neural network (JRNN) based dynamic hand gesture recognition system. A set of allowed gestures is modeled by a sequence of representative static images, i.e., ...

Abstract Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This ...