Three Methods for Energy-Efficient Context Recognition
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Wang, Yi, et al. "A framework of energy efficient mobile sensing for automatic user state recognition." Proceedings of the 7th international conference on Mobile systems, applications, and services. 2009.
Khan, Aftab, et al. "Optimising sampling rates for accelerometer-based human activity recognition." Pattern Recognition Letters 73 (2016): 33-40.
Janko, Vito. Adapting sensor settings for energy-efficient context recognition. Diss. Ph. D. thesis, Jožef Stefan International Postgraduate School, 2020.
Lomax, Susan, and Sunil Vadera. "A survey of cost-sensitive decision tree induction algorithms." ACM Computing Surveys (CSUR) 45.2 (2013): 1-35.
Deb, Kalyanmoy, et al. "A fast and elitist multiobjective genetic algorithm: NSGA-II." IEEE transactions on evolutionary computation 6.2 (2002): 182-197
EECR, https://pypi.org/project/eecr/, Last accessed: 08-03-2021
DOI: https://doi.org/10.31449/inf.v45i2.3509
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