In RSSI-based indoor localization on a six-building campus dataset, an LSTM beat a Set Transformer and other neural baselines, with the Set Transformer consistently second.
Review of rfid-based indoor positioning technology
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Permutation-Invariant Transformer Neural Architectures for Set-Based Indoor Localization Using Learned RSSI Embeddings
In RSSI-based indoor localization on a six-building campus dataset, an LSTM beat a Set Transformer and other neural baselines, with the Set Transformer consistently second.