Complex Human Activity Recognition Based on Spatial LSTM and Deep Residual Convolutional Network Using Wearable Motion Sensors
Author:
Affiliation:
1. Graduate School of Interdisciplinary Information Studies (IIS), The University of Tokyo, Tokyo, Japan
2. Institute of Industrial Science (IIS), The University of Tokyo, Tokyo, Japan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/7361/10599846/10545310.pdf?arnumber=10545310
Reference49 articles.
1. Deep Learning for Intelligent Transportation Systems: A Survey of Emerging Trends
2. Estimating Energy Expenditure Using Body-Worn Accelerometers: A Comparison of Methods, Sensors Number and Positioning
3. A systematic review of smartphone-based human activity recognition methods for health research
4. Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review
5. Integration of positioning and activity context information for lifelog in urban city area
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