Semi-supervised Variational Autoencoder for WiFi Indoor Localization

We address the problem of indoor localization based on WiFi signal strengths. We develop a semi-supervised deep learning method able to train a prediction model from a small set of annotated WiFi observations and a massive set of non-annotated ones. Our method is based on the variational au-toencode...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	International Conference on Indoor Positioning and Indoor Navigation S. 1 - 8
Hauptverfasser:	Chidlovskii, Boris, Antsfeld, Leonid
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.09.2019
Schlagworte:	Buildings Data collection Deep learning Predictive models semi-supervised learning Semisupervised learning Task analysis UJI-IndoorLoc dataset variational auto-encoder WiFi based indoor localization Wireless fidelity
ISSN:	2471-917X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!