Supervised and semi-supervised deep probabilistic models for indoor positioning problems

•The WiFi fingerprint-based positioning problems are investigated.•A hybrid deep learning-based model is introduced.•A deep learning-based semi-supervised model is introduced.•The validation experiments are conducted to demonstrate the effectiveness of the proposed methods. WiFi fingerprint-based in...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 435; S. 228 - 238
Hauptverfasser:	Qian, Weizhu, Lauri, Fabrice, Gechter, Franck
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 07.05.2021
Schlagworte:	Indoor positioning Mixture density networks Semi-supervised learning Variational autoencoders WiFi fingerprints Variational autoencoders Mixture density networks WiFi fingerprints Semi-supervised learning Indoor positioning
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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