A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition
Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatche...
Main Authors: | Yago Saez, Alejandro Baldominos, Pedro Isasi |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2016-12-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/17/1/66 |
Similar Items
-
Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments
by: Alejandro Baldominos, et al.
Published: (2018-04-01) -
A Comparison of Machine Learning and Deep Learning Techniques for Activity Recognition using Mobile Devices
by: Alejandro Baldominos, et al.
Published: (2019-01-01) -
Criteria and Procedures for Estimating the Informativity and Feature Selection in Biomedical Signals for their Recognition
by: A. P. Shulyak, et al.
Published: (2016-09-01) -
Hybridizing Evolutionary Computation and Deep Neural Networks: An Approach to Handwriting Recognition Using Committees and Transfer Learning
by: Alejandro Baldominos, et al.
Published: (2019-01-01) -
Robust RF Mixture Signal Recognition Using Discriminative Dictionary Learning
by: Hao Chen, et al.
Published: (2021-01-01)