Absolute balanced kdtree for fast kNN search.
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Updated
Sep 13, 2023 - C
Absolute balanced kdtree for fast kNN search.
An easy to follow library to make Fortran easier in general with wrapped interfaces, sorting routines, kD-Trees, and other algorithms to handle scientific data and concepts. The library contains core fortran routines and object-oriented classes.
Simple kdtree library in erlang
Object Detection pipeline implemented using the Voxel Grid and ROI based filtering, 3D RANSAC segmentation, Euclidean clustering based on KD-Tree, and bounding boxes, by processing Point Cloud data from LiDAR sensor.
A simple and fast KD-tree for points in Python for kNN or nearest points. (damm short at just ~60 lines) No libraries needed.
Build KD-Trees and perform Nearest Neighbor searches
Project related to the course "Foundations of High Performance Computing" of the Master's Degree in Computational Science and Engineering @ UniTS. The purpose of this assignment is to develop both OpenMP and MPI versions of a program that builds a kdtree.
An optimized, single-header kD-Tree library for points written in C++11.
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Algorithms implemented by me for the course "Advanced Algorithms" (J. Cnops) at the Ghent University (Master of Science in Industrial Engineering: Information Science)
A) Convex Hull 2D-3D Algorithms B) KD-Trees, Orthogonal Search, Voronoi Diagrams, Delaunay Triangulation
Finding nearest city to a position in android using k-d trees
Implementation of KD Trees using scikit learn library for information retrieval.
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