Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond

Author:

Wu Di1ORCID,Yang Jie2ORCID,Sawan Mohamad2ORCID

Affiliation:

1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

2. Center of Excellence in Biomedical Research on Advanced Integrated-on-Chips Neurotechnologies (CenBRAIN Neurotech), School of Engineering, Westlake University, Hangzhou, China

Funder

Zhejiang Key Research and Development Program

Zhejiang Leading Innovative and Entrepreneur Team Introduction Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Reference121 articles.

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2. Improvement of EMG Pattern Recognition Model Performance in Repeated Uses by Combining Feature Selection and Incremental Transfer Learning

3. DeCAF: A deep convolutional activation feature for generic visual recognition;donahue;Proc Int Conf Mach Learn,2014

4. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

5. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc Int Conf Mach Learn,2015

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