Transportation mode classification from smartphone sensors via a long-short-term-memory network
Author:
Affiliation:
1. Carl von Ossietzky University, Oldenburg, Germany
2. OFFIS e.V., Oldenburg, Germany
Funder
Federal Ministry of Education and Research
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3341162.3344855
Reference9 articles.
1. Hristijan Gjoreski Mathias Ciliberto Lin Wang Francisco Javier Ordonez Morales Sami Mekki Stefan Valentin and Daniel Roggen. 2018. The university of sussex-huawei locomotion and transportation dataset for multimodal analytics with mobile devices . IEEE Access 6 (23 July 2018) 42592--42604. Hristijan Gjoreski Mathias Ciliberto Lin Wang Francisco Javier Ordonez Morales Sami Mekki Stefan Valentin and Daniel Roggen. 2018. The university of sussex-huawei locomotion and transportation dataset for multimodal analytics with mobile devices . IEEE Access 6 (23 July 2018) 42592--42604.
2. Long Short-Term Memory
3. Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. CoRR abs/1412.6980 (2015). Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. CoRR abs/1412.6980 (2015).
4. Sensor Placement Variations in Wearable Activity Recognition
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