DRD-SSALNet: A Dual-Representation Decoupled Self-Supervised Active Learning Network for Remote Sensing Semantic Segmentation
The active learning reduces pixel-level annotation costs for remote sensing semantic segmentation, but classifier-dependent sampling is vulnerable to cold-start bias. This letter proposes a dual-representation decoupled self-supervised active learning network (DRD-SSALNet) that separates sampling from classification. T...