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Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation
This method uses the crystal growth in the MBE process to limit the evolution of the level set function, and thus can avoid the re-initialization in the evolution process and regulate the smoothness of the segmented curve.
SaaFormer: Spectral-spatial Axial Aggregation Transformer for Hyperspectral Image Classification
Consequently, the pixel-wise random sampling approach poses a risk of data leakage.
Stationary Point Losses for Robust Model
CE loss sharpens the neural network at the decision boundary to achieve a lower loss, rather than pushing the boundary to a more robust position.
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