AMAR uses a transformer with learnable query embeddings for set-based prediction of concurrent activities from composite Wi-Fi CSI, combined with edge feature extraction and vector quantization for bandwidth-efficient deployment.
WiFi sensing with channel state information: A survey,
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The paper introduces and validates WiLoc, the largest public CSI dataset for machine-learning-based Wi-Fi localization, spanning millions of locations across indoor and outdoor environments.
citing papers explorer
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AMAR: Lightweight Attention-Based Multi-User Activity Recognition from Wi-Fi CSI
AMAR uses a transformer with learnable query embeddings for set-based prediction of concurrent activities from composite Wi-Fi CSI, combined with edge feature extraction and vector quantization for bandwidth-efficient deployment.
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WiLoc: Massive Measured Dataset of Wi-Fi Channel State Information with Application to Machine-Learning Based Localization
The paper introduces and validates WiLoc, the largest public CSI dataset for machine-learning-based Wi-Fi localization, spanning millions of locations across indoor and outdoor environments.