Few-shot learning-based human activity recognition-Reference-Cited by-同舟云学术

Few-shot learning-based human activity recognition

Published:2019-12 Issue: Volume:138 Page:112782
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Feng Siwei^ORCID,Duarte Marco F.^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference41 articles.

1. An effective deep autoencoder approach for online smartphone-based human activity recognition;Almaslukh;International Journal of Computer Science and Network Security,2017

2. Deep learning of representations: Looking forward;Bengio,2013

3. A tutorial on human activity recognition using body-worn inertial sensors;Bulling;ACM Computing Surveys,2014

4. The opportunity challenge: A benchmark database for on-body sensor-based activity recognition;Chavarriaga;Pattern Recognition Letters,2013

5. The Google similarity distance;Cilibrasi;IEEE Transactions on Knowledge and Data Engineering,2007

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