GConvLoc: WiFi Fingerprinting-Based Indoor Localization using Graph Convolutional Networks
SCIE
SCOPUS
- Title
- GConvLoc: WiFi Fingerprinting-Based Indoor Localization using Graph Convolutional Networks
- Authors
- SUH, YOUNG JOO; kim, dongdeok
- Date Issued
- 2023-04
- Publisher
- Oxford University Press
- Abstract
- We propose GConvLoc, a WiFi fingerprinting-based in-door localization method utilizing graph convolutional networks. Using the graph structure, we can consider the fingerprint data of the reference points and their location labels in addition to the fingerprint data of the test point at inference time. Experimental results show that GConvLoc outperforms baseline methods that do not utilize graphs.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/116815
- DOI
- 10.1587/transinf.2022EDL8081
- ISSN
- 0916-8532
- Article Type
- Article
- Citation
- IEICE Transactions on Information and Systems, vol. E106D, no. 4, page. 570 - 574, 2023-04
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- There are no files associated with this item.
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