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Brain tumor segmentation can now maintain accuracy even when crucial MRI data is missing, thanks to a novel diffusion-based imputation strategy.
Injecting semantic knowledge from vision transformer embeddings into guided depth super-resolution models dramatically reduces artifacts and sharpens depth boundaries.
Decoupling spectral reflectance and vegetation indices in a two-stream network beats standard multispectral segmentation, especially when generalizing to new fields and years of barley crops.