ViT-HGR: Vision Transformer-based Hand Gesture Recognition from High Density Surface EMG Signals
Author:
Affiliation:
1. Concordia University,Department of Electrical and Computer Engineering,Montreal,Canada
2. Concordia Institute for Information Systems Engineering (CIISE), Concordia University,Montreal,Canada
Funder
Department of National Defence's Innovation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871489.pdf?arnumber=9871489
Reference26 articles.
1. High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network
2. Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings
3. Movements Classification of Multi-Channel sEMG Based on CNN and Stacking Ensemble Learning
4. Locomo-Net: A Low -Complex Deep Learning Framework for sEMG-Based Hand Movement Recognition for Prosthetic Control
5. An Improved Performance of Deep Learning Based on Convolution Neural Network to Classify the Hand Motion by Evaluating Hyper Parameter
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