Multi-input CNN-GRU based human activity recognition using wearable sensors-Reference-Cited by-同舟云学术

Multi-input CNN-GRU based human activity recognition using wearable sensors

Published:2021-03-10 Issue: Volume: Page:
ISSN:0010-485X
Container-title:Computing
language:en
Short-container-title:Computing

Author:

Dua Nidhi^ORCID,Singh Shiva Nand,Semwal Vijay Bhaskar

Funder

Science and Engineering Research Board

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00607-021-00928-8.pdf

Reference52 articles.

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2. Cornacchia M, Ozcan K, Zheng Y, Velipasalar S (2016) A survey on activity detection and classification using wearable sensors. IEEE Sens J 17:386–403

3. Anguita D, Ghio A, Oneto L, Parra X, Reyes-Ortiz JL (2013) A public domain dataset for human activity recognition using smartphones. In: ESANN

4. Feng Z, Mo L, Li M (2015) A Random Forest-based ensemble method for activity recognition. In: 37th Annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 5074–5077

5. Jain A, Kanhangad V (2017) Human activity classification in smartphones using accelerometer and gyroscope sensors. IEEE Sens J 18(3):1169–1177

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