A computational framework for tracking grain boundaries in 3D image data: Quantifying boundary curvatures and velocities in polycrystalline materials

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Regions with many nearby points keep subdividing. Regions with few or no points stay large. The tree adapts to the data: dense areas get fine-grained cells, sparse areas stay coarse. The split grid is predetermined (always at midpoints), but the tree only refines cells that need it. Sparse regions stay as single large nodes while dense regions subdivide deeply.

Ring-2.5-1T 的表现:

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This letter was organized by a few citizens who are concerned about the potential misuse of AI against Americans. We are not affiliated with any political party, advocacy group, or organization. We are not affiliated with any AI company and are not paid.

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