🕸️🦀 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".

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

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.

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

Header-only C++ K-d tree library

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

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

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

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

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

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

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

Raku package with implementations of the K-Dimensional Tree (KDTree) algorithm.

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.