Synthetic Aperture Radar (SAR) imagery plays a critical role in all-weather, day-and-night remote sensing applications. However, existing SAR-oriented deep learning is constrained by data scarcity, ...

Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...

Abstract: Accurate and interpretable fault diagnosis of wind turbines (WTs) is critical for ensuring reliable and efficient operation. However, existing model-driven and data-driven approaches often ...