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,...

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Detalhes bibliográficos
Principais autores: Juthatip Wisanmongkol, Attaphongse Taparugssanagorn, Le Chung Tran, Anh Tuyen Le, Xiaojing Huang, Christian Ritz, Eryk Dutkiewicz, Son Lam Phung
Formato: Artigo
Idioma:Inglês
Publicado em: Wiley 2022-04-01
coleção:IET Wireless Sensor Systems
Assuntos:
indoor communication
indoor navigation
indoor radio
RSSI
learning (artificial intelligence)
Acesso em linha:https://doi.org/10.1049/wss2.12035
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