Probabilistic von Mises–Fisher representation learning for few-shot remote sensing scene classification
A probabilistic reformulation of FS-RSISC that moves beyond rigid point-based prototypes by modeling each class as a probability distribution over the hyperspherical feature space and adopts the von Mises–Fisher (vMF) distribution to capture both semantic uncertainty and feature diversity.