Amanote Research

Amanote Research

    RegisterSign In

Sparsity-Driven Micro-Doppler Feature Extraction for Dynamic Hand Gesture Recognition

IEEE Transactions on Aerospace and Electronic Systems - United States
doi 10.1109/taes.2017.2761229
Full Text
Open PDF
Abstract

Available in full text

Categories
Electronic EngineeringElectricalAerospace Engineering
Date

April 1, 2018

Authors
Gang LiRui ZhangMatthew RitchieHugh Griffiths
Publisher

Institute of Electrical and Electronics Engineers (IEEE)


Related search

Dynamic Training of Hand Gesture Recognition System

2004English

Real Time Hand Gesture Recognition System for Dynamic Applications

International Journal of UbiComp
2012English

Dynamic Vision Sensor Camera Based Bare Hand Gesture Recognition

Journal of Advanced Computer Science & Technology
2012English

Sparse Representations for Hand Gesture Recognition

2013English

Robust Hand Gesture Recognition With Feature Selection and Hierarchical Temporal Self-Similarities

International Journal of Information and Electronics Engineering
2013English

Real-Time Hand Gesture Recognition

Journal of Computer Science and Cybernetics
2013English

Hand Gesture Recognition Using Surface Electromyogram

Transactions of the Korean Society for Noise and Vibration Engineering
2018English

Dynamic Hand Gesture Recognition Using Hidden Markov Model by Microsoft Kinect Sensor

International Journal of Computer Applications
2016English

Survey Paper on Hand Gesture Recognition

International Journal of Advance Engineering and Research Development
2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy