Research on sEMG-Based Gesture Recognition by Dual-View Deep Learning
Author:
Affiliation:
1. School of Artificial Intelligence, Hebei University of Technology, Tianjin, China
Funder
National Science Foundation of China
Natural Science Foundation of Hebei Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09732991.pdf?arnumber=9732991
Reference44 articles.
1. Analysis of the clustering properties of the Hilbert space-filling curve
2. On the metric properties of discrete space-filling curves
3. A Hilbert Curve Based Representation of sEMG Signals for Gesture Recognition
4. Sur une courbe, qui remplit toute une aire plane
5. On the Use of Deeper CNNs in Hand Gesture Recognition Based on sEMG Signals
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1. NKDFF-CNN: A Convolutional Neural Network with Narrow Kernel and Dual-view Feature Fusion for Multitype Gesture Recognition Based on sEMG;Digital Signal Processing;2024-09
2. Dual Stream Long Short-Term Memory Feature Fusion Classifier for Surface Electromyography Gesture Recognition;Sensors;2024-06-04
3. Unveiling EMG semantics: a prototype-learning approach to generalizable gesture classification;Journal of Neural Engineering;2024-06-01
4. MCMP-Net: MLP combining max pooling network for sEMG gesture recognition;Biomedical Signal Processing and Control;2024-04
5. Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network;Heliyon;2024-03
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