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Time Series Data Augmentation and Dropout Roles in Deep Learning Applied to Fall Detection
| dc.contributor.author | García González, Enol | |
| dc.contributor.author | Villar Flecha, José Ramón | |
| dc.contributor.author | Cal Marín, Enrique Antonio de la | |
| dc.date.accessioned | 2021-02-19T11:19:10Z | |
| dc.date.available | 2021-02-19T11:19:10Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | 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. | |
| dc.identifier.isbn | 978-3-030-57801-5 | |
| dc.identifier.uri | http://hdl.handle.net/10651/57976 | |
| dc.description.sponsorship | 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. | spa |
| dc.format.extent | p. 563-570 | spa |
| dc.language.iso | eng | spa |
| dc.publisher | springer | spa |
| dc.relation.ispartofseries | Advances in Intelligent Systems and Computing; 1268 | |
| dc.rights | © 2020 Springer Nature Switzerland AG. Part of Springer Nature. | |
| dc.title | Time Series Data Augmentation and Dropout Roles in Deep Learning Applied to Fall Detection | spa |
| dc.type | book part | spa |
| dc.identifier.doi | 10.1007/978-3-030-57802-2_54 | |
| dc.relation.projectID | MINECO-TIN2017-84804-R | spa |
| dc.relation.projectID | FCGRUPIN-IDI/2018/000226 | spa |
| dc.relation.publisherversion | http://dx.doi.org/10.1007/978-3-030-57802-2_54 | spa |
| dc.rights.accessRights | open access | |
| dc.type.hasVersion | AM |
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