Improves the generalization capability of multimodal remote sensing imagery by leveraging a probabilistic model based on multi-step Markov noise injection.
Diffusion-Driven Posterior Sampling
Enables intelligent fusion of multimodal data by capturing interactions across spectral, spatial, and frequency domains, delivering more accurate and robust cross-domain insights.
High-Precision Land Cover Segmentation
Enables accurate segmentation for remote sensing land cover classification, achieving state-of-the-art performance across multiple datasets.