Existing deep learning-based hyperspectral anomaly detection methods often overlook frequency domain features, hindering the ability to effectively distinguish between background and anomalies.

A transferable multi-scale convolution domain adaptation network (TMSCDAN) is proposed to achieve feature distribution alignment and extract domain-invariant features under the same working conditions ...