AI-Powered Gesture Recognition for Human Interaction: Enhancing Natural Communication between Humans and Machines
Keywords:
Gesture Recognition, Human-Machine Interaction, AI, CNN-LSTM, Real-time System, Multimodal Input, Usability, Edge Computing.Abstract
The growing demand for natural and intuitive human-machine interaction has drivensignificant advancements in gesture recognition technologies. This study presents an AIpowered gesture recognition framework that leverages a hybrid Convolutional NeuralNetwork–Long Short-Term Memory (CNN-LSTM) architecture to accurately interpret human
References
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Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track
an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV). In 2024 IEEE 14th
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Published
2025-01-02
How to Cite
FNU Harsh, Smarth Behl , Soumya Banerjee. (2025). AI-Powered Gesture Recognition for Human Interaction: Enhancing Natural Communication between Humans and Machines . Journal of Computational Analysis and Applications (JoCAAA), 34(1), 451–463. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2697
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