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Delaunay triangulation is an effective way to build a triangulation of a cloud of points, i.e., a partitioning of the points into simplices (triangles in 2D, tetrahedra in 3D, and so on), such that no two simplices overlap and every point in the set is a
Yahia S. Elshakhs +4 more
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The paper considers a method for representing a set of information objects (scenes) in the field of view of an intelligent robot, based on the fuzzy Delaunay triangulation due to locally regular refinement of the original (coarse) triangular mesh using ...
Vladimir Khramov
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Delaunay-Triangulation-Based Learning With Hessian Total-Variation Regularization
Regression is one of the core problems tackled in supervised learning. Neural networks with rectified linear units generate continuous and piecewise-linear (CPWL) mappings and are the state-of-the-art approach for solving regression problems.
Mehrsa Pourya +2 more
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The objective assessment of the image quality based on the geometrical concentration [PDF]
The method of the objective evaluation of the satellite images based on the calculation of the geometrical concentration using triangulation Delaunay is proposed.
Maltsev Evgenii A. +2 more
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The Interplay of Curvature, Geometry, and Topology Shapes Tissue Organisation in Epithelial Shells
Purely geometric 3D Voronoi models predict the organisation of epithelial shells. The interplay of curvature, geometry, and topology enriches the number of pentagons in shells with lower number of cells. Small MDCK cysts and Mouse embryos match the top polygonal configurations in a compactness‐based ranking derived from the Voronoi model. In conclusion,
Laura Morato +9 more
wiley +1 more source
Plane Delaunay triangulation [PDF]
Delaunay triangulation is one of the fundamental data structures in computational geometry. In the thesis we present the planar Delaunay triangulation and describe its construction.
Števančec, Tadej
core +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
ABSTRACT Medieval and early modern drowned villages in the intertidal zone of the Scheldt estuary (the Netherlands) constitute intriguing yet largely understudied components of north‐western Europe's underwater cultural heritage. Despite their high archaeological potential as time capsules of past settlement landscapes, research has remained limited ...
Jan Trachet +9 more
wiley +1 more source
Objective Systemic sclerosis (SSc) is a chronic autoimmune disorder characterized by immune dysregulation and fibrosis, with myeloid‐derived suppressor cells (MDSCs) emerging as important regulators of immune responses. However, the role of MDSCs in SSc‐associated fibrosis and their interactions with other immune cell populations remain poorly ...
Stefanie Weber +15 more
wiley +1 more source
Flipping geometric triangulations on hyperbolic surfaces
We consider geometric triangulations of surfaces, i.e., triangulations whose edges can be realized by disjoint geodesic segments. We prove that the flip graph of geometric triangulations with fixed vertices of a flat torus or a closed hyperbolic surface
Vincent Despre +2 more
doaj +1 more source

