Abstract: Distance function is a main metrics of measuring the affinity between two data points in machine learning. Extant distance functions often provide unreachable distance values in real ...

After being unsuccessful at finding a pre-written function online, I created my own function for calculating the surface distance between two segmentations in Python. For two image-segmentations, this ...

Loads the raytrace function into your shader. Note that map and steps are required to be defined when using this module. Your signed distance function, responsible for defining the solid shapes in ...

1 Department of Genetic Engineering, Cinvestav Irapuato, Irapuato, Mexico. 2 Department of Biochemistry and Biotechnology, Cinvestav Irapuato, Irapuato, Mexico. Heatmap cluster figures are often used ...

Geodesic distance from a single point on a surface. The heat method allows distance to be rapidly updated for new source points or curves. We introduce the heat method for solving the single- or ...

What if instead of defining a mesh as a series of vertices and edges in a 3D space, you could describe it as a single function? The easiest function would return the signed distance to the closest ...

I will define a new distance function on an unoriented 3D point set and describe how it may be used to reconstruct a surface approximating these points. This distance function is shown to be a ...

3D graphics are made up of little more than very complicated math. With enough time, you could probably compute a ray marching by hand. Or, you could set up Excel to do it for you! Ray marching is a ...

Abstract: The Loss function is an integral component in a Neural network. It affects the performance of CNN network in its classification. In this paper, we propose a Euclidean distance based Loss ...