Stack LSTM-Based User Identification Using Smart Shoes with Accelerometer Data

In this study, we propose a long short-term memory (LSTM)-based user identification method using accelerometer data from smart shoes. In general, for the user identification with human walking data, we require a pre-processing stage in order to divide human walking data into individual steps. Next,...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Do-Yun, Lee, Seung-Hyeon, Jeong, Gu-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662428/
https://www.ncbi.nlm.nih.gov/pubmed/34884133
http://dx.doi.org/10.3390/s21238129

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662428/
https://www.ncbi.nlm.nih.gov/pubmed/34884133
http://dx.doi.org/10.3390/s21238129

Ejemplares similares