Multiscale Deep Feature Learning for Human Activity Recognition Using Wearable Sensors
Author:
Affiliation:
1. School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, China
2. School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/41/9913345/09744439.pdf?arnumber=9744439
Reference34 articles.
1. Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors
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3. Asymmetric Residual Neural Network for Accurate Human Activity Recognition
4. Deep activity recognition models with triaxial accelerometers;alsheikh;Proc Workshops 30th AAAI Conf Artif Intell,0
5. The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
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