Acknowledgement
Supported by : 한국외국어대학교
References
- A. Avci, S. Bosch, M. Marin-Perianu, R. Marin-Perianu, and P. Havinga, "Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey," Archit. Comput. Syst. (ARCS), 2010 23rd Int. Conf., pp. 1-10, 2010.
- J. Yin, Q. Yang, J. J. Pan, Jie Yin, Qiang Yang, and J. J. Pan, "Sensor-based abnormal human-activity detection," IEEE Trans. Knowl. Data Eng., vol. 20, no. 8, pp. 1082-1090, 2008. https://doi.org/10.1109/TKDE.2007.1042
- S. Chernbumroong, S. Cang, and H. Yu, "Genetic algorithm-based classifiers fusion for multisensor activity recognition of elderly people," IEEE J. Biomed. Heal. Informatics, vol. 19, no. 1, pp. 282-289, Jan. 2015. https://doi.org/10.1109/JBHI.2014.2313473
- D. Guan, W. Yuan, Y.-K. Lee, A. Gavrilov, and S. Lee, "Activity Recognition Based on Semi-supervised Learning," in 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), 2007, pp. 469-475.
- Z. Huang, Z. Pan, and B. Lei, "Transfer learning with deep convolutional neural network for SAR target classification with limited labeled data," Remote Sensing, vol. 9, p.907, 2017 https://doi.org/10.3390/rs9090907
- R. Caruana, "Multitask Learning," Mach. Learn., vol. 28, no. 1, pp. 41-75, 1997. https://doi.org/10.1023/A:1007379606734
- M. Kandemir, A. Vetek, M. Gonen, A. Klami, and S. Kaski, "Multi-task and multi-view learning of user state," Neurocomputing, vol. 139, pp. 97-106, Sep. 2014. https://doi.org/10.1016/j.neucom.2014.02.057
- Y. Xue, X. Liao, L. Carin, and B. Krishnapuram, "Multi-Task Learning for Classification with Dirichlet Process Priors," J. Mach. Learn. Res., vol. 8, no. Jan, pp. 35-63, 2007.
- A. Niculescu-Mizil and R. Caruana, "Predicting good probabilities with supervised learning," in Proceedings of the 22nd international conference on Machine learning - ICML '05, 2005, pp. 625-632.
- L. Hu, Y. Chen, J. Wang, C. Hu, and X. Jiang, "OKRELM: online kernelized and regularized extreme learning machine for wearable-based activity recognition," Int. J. Mach. Learn. Cybern., vol. 9, no. 9, pp. 1577-1590, Sep. 2018. https://doi.org/10.1007/s13042-017-0666-8
- A. Blum and T. Mitchell, "Combining labeled and unlabeled data with co-training," in Proceedings of the eleventh annual conference on Computational learning theory - COLT' 98, 1998, pp. 92-100
- D. Anguita, A. Ghio, L. Oneto, X. Parra, and J. L. Reyes-Ortiz, "A Public Domain Dataset for Human Activity Recognition Using Smartphones," in European Symposium on Artificial Neural Networks, 2013.
- D. Roggen et al., "Collecting complex activity datasets in highly rich networked sensor environments," in 2010 Seventh International Conference on Networked Sensing Systems (INSS), 2010, pp. 233-240