arXiv (OAI Expanded)
open access
Cross-Domain Inference for Human Localization: Applying Wi-Fi RSSI Data to CSI-Trained Models
Wi-Fi signal data can be used to compromise the privacy of individuals. While many existing approaches rely on Channel State Information (CSI), collecting this data on typical IoT devices often requires elevated operating system permissions and specialized drivers. Consequently, this paper investiga
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Cross-Domain Inference for Human Localization: Applying Wi-Fi RSSI Data to CSI-Trained Models#919243
- FuseFi: Combining Irregularly Sampled CSI from Diverse Communication Packets and Frequency Bands for Wi-Fi Sensing#1011022
- DoRF++: Spherical Representation Learning over Doppler Radiance Fields for Robust Wi-Fi Sensing#1048768
- Domain Generalization for Smartphone-Based Human Activity Recognition: A Systematic Analysis of Components and Interactions#1084777
- Privacy for free in the overparameterized regime#211268
Record · ID 1123586
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive