Time Series Data Augmentation and Dropout Roles in Deep Learning Applied to Fall Detection
Publication date:
2021
Editorial:
springer
Publisher version:
Citación:
González E.G., Villar J.R., de la Cal E. (2021) Time Series Data Augmentation and Dropout Roles in Deep Learning Applied to Fall Detection. En: Herrero Á., Cambra C., Urda D., Sedano J., Quintián H., Corchado E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020.
Serie:
Advances in Intelligent Systems and Computing; 1268
Descripción física:
p. 563-570
ISBN:
978-3-030-57801-5
Patrocinado por:
This research has been funded by the Spanish Ministry of Science and Innovation under project MINECO-TIN2017-84804-R and by the Grant FCGRUPIN-IDI/2018/000226 project from the Asturias Regional Government.
Collections
- Capítulos de libros [6511]
- Informática [872]
- Investigaciones y Documentos OpenAIRE [8366]
Files in this item
Métricas
Compartir
