Semi-Supervised Learning-Enhanced Fingerprint Indoor Positioning by Exploiting an Adapted Mean Teacher Model

Semi-Supervised Learning-Enhanced Fingerprint Indoor Positioning by Exploiting an Adapted Mean Teacher Model

Location awareness is crucial for numerous emerging wireless indoor applications. Deep learning algorithms have demonstrated the potential for achieving the required level of positioning accuracy in indoor environments. However, obtaining abundant labels for data-driven machine learning is costly in...

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Bibliographic Details
Main Authors: Peng Chen, Yingzhi Liu, Wei Li, Jingyi Wang, Jianxiu Wang, Bei Yang, Gang Feng
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Electronics
Subjects:
indoor positioning
channel impulse response
heavy non-line-of-sight
deep learning
semi-supervised learning
Online Access:https://www.mdpi.com/2079-9292/13/2/298

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https://www.mdpi.com/2079-9292/13/2/298

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