Social inclusion in ambient assisted living environments: Home automation and convenience services for elderly users, Proceedings of the International Conference on Artificial Intelligence, pp.55-59, 2011. ,
Sensor-Based Activity Recognition, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol.42, issue.6, pp.790-808, 2012. ,
DOI : 10.1109/TSMCC.2012.2198883
Introduction to MAchine Learning & Knowledge Extraction (MAKE), Machine Learning and Knowledge Extraction, vol.15, issue.1, pp.1-20, 2017. ,
DOI : 10.1007/978-3-642-40511-2_22
Limitedmemory warping lcss for real-time low-power pattern recognition in wireless nodes, European Conference on Wireless Sensor Networks, pp.151-167, 2015. ,
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.838-845, 2005. ,
DOI : 10.1109/CVPR.2005.61
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations, Proceedings of the 26th Annual International Conference on Machine Learning, ICML '09, pp.609-616, 2009. ,
DOI : 10.1145/1553374.1553453
Unsupervised feature learning for audio classification using convolutional deep belief networks Advances in neural information processing systems, pp.1096-1104, 2009. ,
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups, IEEE Signal Processing Magazine, vol.29, issue.6, pp.82-97, 2012. ,
DOI : 10.1109/MSP.2012.2205597
Human activity recognition from wireless sensor network data: Benchmark and software. Activity recognition in pervasive intelligent environments, pp.165-186, 2011. ,
A Data-Driven Approach for Event Prediction, Computer Vision?ECCV, pp.2010-707, 2010. ,
DOI : 10.1007/978-3-642-15552-9_51
KCAR: A knowledge-driven approach for concurrent activity recognition, Pervasive and Mobile Computing, vol.19, pp.47-70, 2015. ,
DOI : 10.1016/j.pmcj.2014.02.003
Activity Recognition in the Home Using Simple and Ubiquitous Sensors, International Conference on Pervasive Computing, pp.158-175, 2004. ,
DOI : 10.1007/978-3-540-24646-6_10
Activity Recognition from User-Annotated Acceleration Data, International Conference on Pervasive Computing, pp.1-17, 2004. ,
DOI : 10.1007/978-3-540-24646-6_1
URL : http://web.media.mit.edu/~intille/papers-files/BaoIntille04.pdf
Accurate activity recognition in a home setting, Proceedings of the 10th international conference on Ubiquitous computing, UbiComp '08, pp.1-9, 2008. ,
DOI : 10.1145/1409635.1409637
Classification Accuracies of Physical Activities Using Smartphone Motion Sensors, Journal of Medical Internet Research, vol.11, issue.1, p.130, 2012. ,
DOI : 10.1145/1656274.1656278
Context-Aware Activity Recognition and Anomaly Detection in Video, IEEE Journal of Selected Topics in Signal Processing, vol.7, issue.1, pp.91-101, 2013. ,
DOI : 10.1109/JSTSP.2012.2234722
Nursing Homes in 10 Nations: A Comparison Between Countries and Settings, Age and Ageing, vol.26, issue.suppl 2, pp.3-12, 1997. ,
DOI : 10.1093/ageing/26.suppl_2.3
Long short-term memory recurrent neural network architectures for large scale acoustic modeling, Fifteenth Annual Conference of the International Speech Communication Association, 2014. ,
Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997. ,
DOI : 10.1016/0893-6080(88)90007-X
Learning to Forget: Continual Prediction with LSTM, Neural Computation, vol.3, issue.10, pp.2451-2471, 2000. ,
DOI : 10.1162/neco.1990.2.4.490
Learning precise timing with lstm recurrent networks, Journal of machine learning research, vol.3, pp.115-143, 2002. ,
Bidirectional long short-term memory networks for relation classification, In: PACLIC, 2015. ,
Adam: A method for stochastic optimization. arXiv preprint arXiv:1412, p.6980, 2014. ,
Dropout as a bayesian approximation: Representing model uncertainty in deep learning, Proceedings of The 33rd International Conference on Machine Learning (ICML) ,