On the Application of Graph Neural Networks for Indoor Positioning Systems-Reference-Cited by-同舟云学术

On the Application of Graph Neural Networks for Indoor Positioning Systems

Published:2023 Issue: Volume: Page:239-256
ISSN:
Container-title:Machine Learning for Indoor Localization and Navigation
language:
Short-container-title:

Author:

Lezama Facundo,Larroca Federico,Capdehourat Germán

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-26712-3_10

Reference40 articles.

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2. Basri C, El Khadimi A (2016) Survey on indoor localization system and recent advances of wifi fingerprinting technique. In: 2016 5th international conference on multimedia computing and systems (ICMCS). IEEE, pp 253–259

3. Bracco A, Grunwald F, Navcevich A, Capdehourat G, Larroca F (2020) Museum accessibility through wi-fi indoor positioning. Preprint. arXiv:200811340

4. Chen B, Chang RY (2022) Few-shot transfer learning for device-free fingerprinting indoor localization. CoRR abs/2201.12656. https://arxiv.org/abs/2201.12656, https://doi.org/2201.126562201.12656

5. Chiou M, Liu Z, Yin Y, Liu A, Zimmermann R (2020) Zero-shot multi-view indoor localization via graph location networks. In: MM ’20: The 28th ACM international conference on multimedia, virtual event/Seattle, WA, USA, October 12–16, 2020. ACM, pp 3431–3440. https://doi.org/10.1145/3394171.3413856

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