A new cross-modal learning method aligns WiFi fingerprint traces and inertial displacement traces in a shared latent space with additive structure to enable relative localization under weak supervision.
An encoded lstm network model for wifi-based indoor positioning,
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Learning Displacement-Aware WiFi Representations for Weakly Supervised Relative Localization
A new cross-modal learning method aligns WiFi fingerprint traces and inertial displacement traces in a shared latent space with additive structure to enable relative localization under weak supervision.