An ensemble approach to deep‐learning‐based wireless indoor localization

Abstract The authors investigate the use of deep learning in wireless indoor localization to address the shortcomings of the existing range‐based (e.g. trilateration and triangulation) and range‐free (e.g. fingerprinting) localization. Instead of relying on geometric models and hand‐picked features,...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Juthatip Wisanmongkol, Attaphongse Taparugssanagorn, Le Chung Tran, Anh Tuyen Le, Xiaojing Huang, Christian Ritz, Eryk Dutkiewicz, Son Lam Phung
Formato: Artigo
Lenguaje:Inglês
Publicado: Wiley 2022-04-01
Colección:IET Wireless Sensor Systems
Materias:
indoor communication
indoor navigation
indoor radio
RSSI
learning (artificial intelligence)
Acceso en línea:https://doi.org/10.1049/wss2.12035
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares