E3S Web Conf.
Volume 202, 2020The 5th International Conference on Energy, Environmental and Information System (ICENIS 2020)
|Number of page(s)||12|
|Section||Smart Information System|
|Published online||10 November 2020|
- E.D. Franco, P.A. Colpas, J.M. Quero, M. Espinilla, Sensor Based Datasets for Human Activity Recognition – A Systematic Review of Literature, International Journal of Computer Science, 2169-3536, (2018) [Google Scholar]
- M. Vrigas, C. Nikou, A. Kakadiaris, A Review of Human Activity Recognition Methods, Frontiers in Robotic and Artificial Intelligent, (2015) [Google Scholar]
- Z.A. Khan, W. Sohn, A Hierarchical Abnormal Human Activity Recognition System Based on R-transform and Kernel Discriminant Analysis for Elderly Health Care, Computing 95, 109-127, (2013) [CrossRef] [Google Scholar]
- J.L, Candas, V. Pelaez, G. Lopez, M.A. Fernandez, E. Alvarez, G. Diaz, An Automatic Data Mining Method to Detect Abnormal Human Behaviour using Physical Activity Measurements, Pervasive and Mobile Computing 15, 228-241, (2015) [Google Scholar]
- L. Xiantao, Y. Sun, L. Gong, L. Zheng, K. Chen, Y. Zhou, Y. Gu, Y. Xu, Q. Guo, Z. Hong, D. Dhing, J. Fu, Q. Zhao, A Novel Homozygous Mutation in TREM2 found in a Chinese early-onset Dementia Family with Mild Bone Involvement, Neurobiology of Aging, (2019) [Google Scholar]
- C. Dhiman, D.K. Vishwakarma, A Review of state-of-the-art Techniques for Abnormal Human Activity Recognition, Engineerring Applications of Artificial Intelligence 77, 21-45, (2019) [CrossRef] [Google Scholar]
- D. Arifoglu, A. Bouchechia, Activity Recognition and Abnormal Behaviour Detection with Recurrent Neural Network, International Conference on Mobile Systems and Pervasive Computing, 110, 86-93, (2017) [Google Scholar]
- D. Singh, E. Merdivan, S. Hanke, J. Kropf, M. Geist, A. Holzinger, Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment, Integrative Machine Learning, (2017) [Google Scholar]
- Z. Chang, Y. Zhang, W. Chen, Electric Price Prediction based on Hybrid Model of Adam Optimized LSTM Neural Network and Wavelet Transform, International Journal of Energy Research, (2019) [Google Scholar]
- A. Almeida, G. Azkune, Predicting Human Behaviour with Recurrent Neural Networks, Applied Sciences 8, 2, (2018) [CrossRef] [Google Scholar]
- W. Yu, X. Li, J. Gonzalez, Fast Training of Deep Learning LSTM Networks, International Symposium on Neural Networks, 3-10, (2019) [Google Scholar]
- B. Warsito, H. Yasin, A. Prahutama, Particle Swarm Optimization versus Gradient Based Methods in Optimizing Neural Network, Journal of Physics: Conference Series 1217, (2019) [Google Scholar]
- A. Wibowo, D. Setianto, P.W. Wisnu, W. Jatmiko, Optimization of Backpropagation Using Nguyen-Widrow and Stimulus-Sampling for Breast Cancer Classification and Feature Selection, Journal of Engineerring Science and Technology 6, 3437-3456, (2019) [Google Scholar]
- V. Kasteren, A. Noulas, G. Englebienne, B. Krose, Accurate Activity Recognition in a Home Setting, Proceeding of the 10th International Conference on Ubiquitos Computing (2008) [Google Scholar]
- N.S. Keskar, R. Socher, Improving Generalization Perfromance by Switching from Adam to SGD, (2017) [Google Scholar]
- J. Duchi, E. Hazan, Y. Singer, Adaptive Subgradient Methods for Online Learning and Stochastic Optimization, Journal of Machine Learning Research 12, 2121-2159, (2011) [Google Scholar]
- M.D. Zeiler, ADADELTA: An Adaptive Learning Rate Method, arXiv preprint arXiv:1212.5701, (2012) [Google Scholar]
- T. Tieleman, E. Hinton, COURSERA: Neural Networks for Machine Learning, (2012) [Google Scholar]
- D. Kingma, J. Ba, Adam: A Method for Stochastic Optimization, Proceeding of International Conference on Learning Representations, (2015) [Google Scholar]
- A. Wibowo, P.W. Wiryawan, N.I. Nuqoyati, Optimization of Neural Network for Cancer MicroRNA Biomarkers Classification, Journal of Physics: Conference Series, 1217, (2019) [Google Scholar]
- T. Mikolov, I. Sutskever, K. Chen, G. Corrado, Dean, D. Jeffrey, Distributed Representations of Words and Phrases and their Compositionality, In Advanced in Neural Information Processing Systems, 3111-3119, (2013) [Google Scholar]
- S. Hochreiter, J. Schmidhuber, Long Short Term Memory, Neural Computation, 9, 1735-1780, (1997) [Google Scholar]
- K. Greff, K. Rupesh, Srivastava, J. Koutnik, R. Bas, Steunebrink, J. Schmidhuber, LSTM: A Search Space Odyssey, Transactions on Neural Networks and Learning Systems, (2017) [Google Scholar]
- R.D. Shirwaikar, D.U. Acharya, K. Makkithaya, Optimizing Neural Networks for Medical Data Sets: A Case Study on Neonal Apnea Prediction, Artificial Intelligent In Medicine 98, 59-76, (2019) [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.