A Transferred Daily Activity Recognition Method Based on Sensor Sequences-Reference-Cited by-同舟云学术

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A Transferred Daily Activity Recognition Method Based on Sensor Sequences

Published:2022-07-11 Issue:2 Volume:55 Page:1001-1028
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Guo Jinghuan,Ren Jianxun,Chen Haoming,Han Shuo,Li Shaoxi

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-022-10923-5.pdf

Reference34 articles.

1. Abidine BM, Fergani L, Fergani B, Oussalah M (2018) The joint use of sequence features combination and modified weighted SVM for improving daily activity recognition. Pattern Anal Appl. https://doi.org/10.1007/s10044-016-0570-y

2. Lu Lu, Qing-ling C, Yi-Ju Z (2017) Activity recognition in smart homes. Multimedia Tools Appl. https://doi.org/10.1007/s11042-016-4197-1

3. Saeedi R, Gebremedhin AH (2020) A signal-level transfer learning framework for autonomous reconfiguration of wearable systems. IEEE Trans Mob Comput. https://doi.org/10.1109/TMC.2018.2878673

4. Wang J, Chen Y, Hu L, Peng X, Yu PS (2018) Stratified transfer learning for cross-domain activity recognition. In: 2018 IEEE international conference on pervasive computing and communications (PerCom). https://doi.org/10.1109/PERCOM.2018.8444572

5. Alam MR, Reaz MBI, Ali MAM (2012) A review of smart homes—past, present, and future. IEEE Trans Syst Man Cybernet Part C. https://doi.org/10.1109/TSMCC.2012.2189204

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