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Human activity recognition (HAR) in ubiquitous computing is beginning to adopt deep learning to substitute for well-established analysis techniques that rely on hand-crafted feature extraction and classification techniques.
Long short-term memory
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Gradient flow in recurrent nets: the difficulty of learning long-term dependencies, 2001
Sepp Hochreiter, Yoshua Bengio, Paolo Frasconi, and Jürgen Schmidhuber · 2001
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Potentials of enhanced context awareness in wearable assistants for parkinson’s disease patients with the freezing of gait syndrome
Marc Bachlin, Daniel Roggen, Gerhard Troster, Meir Plotnik, Noit Inbar, Inbal Meidan, Talia Herman, Marina Brozgol, Eliya Shaviv, Nir Giladi, et al · 2009
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Torch7: A matlab-like environment for machine learning
Ronan Collobert, Koray Kavukcuoglu, and Clément Farabet · 2011
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John Duchi, Elad Hazan, and Yoram Singer · 2011
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Feature learning for activity recognition in ubiquitous computing
Thomas Plötz, Nils Y Hammerla, and Patrick Olivier · 2011
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Automatic assessment of problem behavior in individuals with developmental disabilities
Thomas Plötz, Nils Y Hammerla, Agata Rozga, Andrea Reavis, Nathan Call, and Gregory D Abowd · 2012
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Introducing a new benchmarked dataset for activity monitoring
Attila Reiss and Didier Stricker · 2012
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The opportunity challenge: A benchmark database for on-body sensor-based activity recognition
Ricardo Chavarriaga, Hesam Sagha, Alberto Calatroni, Sundara Tejaswi Digumarti, Gerhard Tröster, José del R Millán, and Daniel Roggen · 2013
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A tutorial on human activity recognition using body-worn inertial sensors
Andreas Bulling, Ulf Blanke, and Bernt Schiele · 2014
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An efficient approach for assessing hyperparameter importance
Frank Hutter, Holger Hoos, and Kevin Leyton-Brown · 2014
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Convolutional neural networks for human activity recognition using mobile sensors
Ming Zeng, Le T Nguyen, Bo Yu, Ole J Mengshoel, Jiang Zhu, Pang Wu, and Juyong Zhang · 2014
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Deep activity recognition models with triaxial accelerometers
Mohammad Abu Alsheikh, Ahmed Selim, Dusit Niyato, Linda Doyle, Shaowei Lin, and Hwee-Pink Tan · 2015
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Deepear: robust smartphone audio sensing in unconstrained acoustic environments using deep learning
Nicholas D Lane, Petko Georgiev, and Lorena Qendro · 2015
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Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
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Learning human identity from motion patterns
Natalia Neverova, Christian Wolf, Griffin Lacey, Lex Fridman, Deepak Chandra, Brandon Barbello, and Graham Taylor · 2015
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Convolutional neural network for stereotypical motor movement detection in autism
Nastaran Mohammadian Rad, Andrea Bizzego, Seyed Mostafa Kia, Giuseppe Jurman, Paola Venuti, and Cesare Furlanello · 2015
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Deep convolutional neural networks for human activity recognition with smartphone sensors
Charissa Ann Ronao and Sung-Bae Cho · 2015
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Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R Steunebrink, and Jürgen Schmidhuber · 2015
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Draw: A recurrent neural network for image generation
Karol Gregor, Ivo Danihelka, Alex Graves, and Daan Wierstra · 2015
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Let’s (not) stick together: pairwise similarity biases cross-validation in activity recognition
Nils Y Hammerla and Thomas Plötz · 2015
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Pd disease state assessment in naturalistic environments using deep learning
Nils Y Hammerla, James M Fisher, Peter Andras, Lynn Rochester, Richard Walker, and Thomas Plötz · 2015
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Evaluation of deep convolutional neural network architectures for human activity recognition with smartphone sensors
Charissa Ann Ronaoo and Sung-Bae Cho · 2015
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Deep convolutional neural networks on multichannel time series for human activity recognition
Jian Bo Yang, Minh Nhut Nguyen, Phyo Phyo San, Xiao Li Li, and Shonali Krishnaswamy · 2015
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Human activity recognition with hmm-dnn model
Licheng Zhang, Xihong Wu, and Dingsheng Luo · 2015
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Deep convolutional and lstm recurrent neural networks for multimodal wearable activity recognition
Francisco Javier Ordóñez and Daniel Roggen · 2016
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