The D-CNN-LSTM Autoencoder method optimizes the anomaly detection rate for all of the anomalies, specifically in the case of low magnitude anomalies, enhancing F1-score up to 18.12% in single types of ...

In this paper, a signal-guided masked autoencoder (S-MAE) based semi-supervised learning framework is proposed for high-precision positioning with limited labeled channel impulse response (CIR) ...