k-d-tree

🕸️🦀 A WASM vector similarity search written in Rust

Geo Assist is a spatial library to manage spatial data in-memory.

K-D Tree Boids on Bevy

C++ implementations of two multi-threaded, k-d tree-building algorithms that build either a k-d tree, which implements a set, or a k-d tree-based key-to-multiple-value map. Multi-threaded algorithms are included for region search, nearest-neighbor search, and reverse-nearest-neighbor search.

nanoflann wrapper for python and maybe fortran

Data and algorithms used in empirical contribution of the research project "The Impact of Physicality on Network Structure".

Header-only C++ K-d tree library

This is the public repository for the "No-collision Transportation Maps" paper.

Guía de Árboles K-D + Implementación en python para encontrar el Tizoncito más cercano a una ubicación de consulta dadas sus coordenadas geográficas. Considera 18 sucursales en la CDMX y usa algoritmo KNN (k nearest neighbor) para encontrar los más cercanos.

Java WSDL-based SOAP web service with Springboot (Spring-WS, Contract first) and nearest neighbor search

A package for creating hybrid solar system catalogues for making LSST predictions

A CPU-based path tracer built in C++. Capable of rendering photorealistic scenes with depth of field and global illumination.

rust k-d tree implementation, and a pure-rust colordeposit as an example/benchmark

By applying K-D trees data structure, the program would do the map search based on provided x and y coordinates.

Parallelize constructing k-D tree and performing k-NN using a thread pool

This project estimates tree crown volumes using 3D modeling and high-resolution LiDAR datasets (AHN4 and Kavel_10) in Nijmegen, Netherlands. The study focuses on tree detection, biophysical parameter estimation, and crown volume mapping, highlighting applications in urban green space management and ecosystem services. Tools: Python, LiDAR, GIS soft

A simple generic k-d tree implementation.

A balanced k-d tree which can partition three-dimensional space to organize/insert objects. Search operation is also available.

An API to find the best partner to deliver beverages to our customers, providing the best and fastest service. To achieve this our compute fleet deals with GIS objects all the time.

a specific data structure for efficiently representing our data. In particular, KD-trees helps organize and partition the data points based on specific conditions.💥🦄