Toward Realistic Remote Sensing Dataset Distillation with Discriminative Prototype-guided Diffusion

Recent years have witnessed the remarkable success of deep learning in remote sensing image interpretation, driven by the availability of large-scale benchmark datasets. However, this reliance on massive training data also brings substantial storage and computational costs. To address this challenge