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A Reliability-Aware Boundary Refinement Network (RABR-Net), a two-stage framework for trustworthy image segmentation that provides an interpretable and reliability-focused strategy for boundary-sensitive biomedical image segmentation.
PCA-DMD provides a scalable operator-theoretic framework that segments LFP recordings into overlapping windows, projects them into a compact PCA space, learns linear Koopman evolution in the latent space, and reconstructs continuous signals through inverse projection and overlap-add aggregation.
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