Xiang-Sen Cui

A Practical Fixed-Configuration, Training-Free Baseline for Within-Sensor Hyperspectral Anomaly Detection

Hyperspectral anomaly detection (HAD) aims to identify rare targets without labeled anomaly samples, but many recent deep HAD approaches require scene-specific neural optimization, increasing deployment cost. This paper presents MASCR-UAF, a fixed-configuration baseline designed for training-free within-sensor HAD. Glo...