sEMG Signal Generation for Data Augmentation Using Time Series Transformer Based Conditional GAN-Reference-Cited by-同舟云学术

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sEMG Signal Generation for Data Augmentation Using Time Series Transformer Based Conditional GAN

Published:2023-10-12 Issue: Volume: Page:
ISSN:
Container-title:2023 Seventh International Conference on Advances in Biomedical Engineering (ICABME)
language:
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Author:

Nasrallah Chawki¹,Boudaoud Sofiane¹,Laforet Jeremy¹,Chazard Emmanuel²,Beuscart Jean-Baptiste²,Istrate Dan¹

Affiliation:

1. Alliance Sorbonne Université, Université de technologie de Compiègne,Laboratoire de Biomécanique et de Bioingénierie UMR CNRS 7338,Comniègne,France

2. Univ. Lille,CHU Lille ULR 2694- METRICS, CERIM,Public health dept,Lille,France,F-59000

Funder

CNRS

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10292995/10292942/10293077.pdf?arnumber=10293077

Reference12 articles.

1. Automatic Target Recognition for Low Resolution Foliage Penetrating SAR Images Using CNNs and GANs

2. Active aging prediction from muscle electrical activity using HD-sEMG signals and machine learning

3. SMOTE: Synthetic Minority Over-sampling Technique

4. Generative Adversarial Networks;goodfellow;ArXiv,2014

Cited by 1 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. TranSEMG: A Trans-Scale Hybrid Model for High-Accurate Hip Joint Moment Prediction;IEEE Transactions on Instrumentation and Measurement;2024

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