Multi-Channel sEMG Signal Gesture Recognition Based on Improved CNN-LSTM Hybrid Models-Reference-Cited by-同舟云学术

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Multi-Channel sEMG Signal Gesture Recognition Based on Improved CNN-LSTM Hybrid Models

Published:2021-03-04 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Intelligence and Safety for Robotics (ISR)
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Author:

Bai Dianchun,Liu Tie,Han Xinghua,Chen Guo,Jiang Yinlai,Hiroshi Yokoi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9419481/9419375/09419532.pdf?arnumber=9419532

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fusion inception and transformer network for continuous estimation of finger kinematics from surface electromyography;Frontiers in Neurorobotics;2024-05-03

2. FFCSLT: A Deep Learning Model for Traffic Police Hand Gesture Recognition Using Surface Electromyographic Signals;IEEE Sensors Journal;2024-04-15

3. Transformer-based network with temporal depthwise convolutions for sEMG recognition;Pattern Recognition;2024-01

4. Stretchable array electromyography sensor with graph neural network for static and dynamic gestures recognition system;npj Flexible Electronics;2023-04-12

5. DeepTPA-Net: A Deep Triple Attention Network for sEMG-Based Hand Gesture Recognition;IEEE Access;2023

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