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Found 7 papers, 0 papers with code
SALC: Skeleton-Assisted Learning-Based Clustering for Time-Varying Indoor Localization
Both simulation and experimental results demonstrate that the proposed SALC system can effectively reconstruct the fingerprint database with an enhanced location estimation accuracy, which outperforms the other existing schemes in the open literature.
Time-Selective RNN for Device-Free Multi-Room Human Presence Detection Using WiFi CSI
In this paper, we propose a device-free human presence detection system for multi-room scenarios using a time-selective conditional dual feature extract recurrent network (TCD-FERN).
Attention-Enhanced Deep Learning for Device-Free Through-the-Wall Presence Detection Using Indoor WiFi Systems
Overall, our proposed ALPD system shows promising results for human presence detection using WiFi CSI signals.
Attention-based Learning for Sleep Apnea and Limb Movement Detection using Wi-Fi CSI Signals
In this paper, we propose the attention-based learning for sleep apnea and limb movement detection (ALESAL) system that can jointly detect sleep apnea and PLMD under different sleep postures across a variety of patients.
A New Paradigm for Device-free Indoor Localization: Deep Learning with Error Vector Spectrum in Wi-Fi Systems
The demand for device-free indoor localization using commercial Wi-Fi devices has rapidly increased in various fields due to its convenience and versatile applications.
BTS: Bifold Teacher-Student in Semi-Supervised Learning for Indoor Two-Room Presence Detection Under Time-Varying CSI
Furthermore, BTS outperforms existing SSL-based models in terms of the highest detection accuracy while achieving the asymptotic performance of SL-based methods.
CRONOS: Colorization and Contrastive Learning for Device-Free NLoS Human Presence Detection using Wi-Fi CSI
In this work, we propose a system called CRONOS (Colorization and Contrastive Learning Enhanced NLoS Human Presence Detection), which generates dynamic recurrence plots (RPs) and color-coded CSI ratios to distinguish mobile and stationary people from vacancy in a room, respectively.
