Improved SMOTE Algorithm to Deal with Imbalanced Activity Classes in Smart Homes-Reference-Cited by-同舟云学术

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Improved SMOTE Algorithm to Deal with Imbalanced Activity Classes in Smart Homes

Published:2018-10-29 Issue:2 Volume:50 Page:1503-1526
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Guo Shikai,Liu Yaqing,Chen Rong,Sun Xiao,Wang Xiangxin

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

ANHUI Province Key Laboratory of Affective Computing & Advanced Intelligent Machine

the Open Project Program of Artificial Intelligence Key Laboratory of Sichuan Province

Publisher

Springer Science and Business Media LLC

Subject

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

Link

http://link.springer.com/content/pdf/10.1007/s11063-018-9940-3.pdf

Reference47 articles.

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2. Bloch F, Gautier V, Noury N, Lundy JE, Poujaud J, Claessens YE, Rigaud AS (2011) Evaluation under real-life conditions of a stand-alone fall detector for the elderly subjects. Ann Phys Rehabil Med 54:391–398

3. Arcelus A, Herry CL, Goubran RA, Knoefel F (2009) Determination of sit-to-stand transfer duration using bed and floor pressure sequences. IEEE Trans Bio-med Eng 56(10):2485–2492

4. Shen J, Chang S, Shen J, Liu Q, Sun X (2016) A lightweight multi-layer authentication protocol for wireless body area networks. Fut Gen Comput Syst. https://doi.org/10.1016/j.future.2016.11.033

5. Sun Y, Gu F (2017) Compressive sensing of piezoelectric sensor response signal for phased array structural health monitoring. Int J Sens Netw 23(4):258–264

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