ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python

A collection of GTSAM factors and optimizers for point cloud SLAM

Fast Near-Duplicate Image Search and Delete using pHash, t-SNE and KDTree.

A k-d tree implementation in Go.

A Rust crate and Python library for packed, static, zero-copy spatial indexes.

Probably the fastest C++ dbscan library.

Golang k-D tree implementation with duplicate coordinate support

A Julia package for downloading and analysing geospatial data from OpenStreetMap APIs.

A C++ header only library for fast nearest neighbor and range searches using a KdTree. It supports interfacing with Eigen, OpenCV, and custom data types and provides optional Python bindings.

Unofficial python wrapper to the nanoflann k-d tree

generic DBSCAN on CPU & GPU

Implementations of different algorithms for building Euclidean minimum spanning tree in k-dimensional space.

A Fortran implementation of KD-Tree searching

LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".

Hybrid Spatial Data Structure based on Quad Tree, R Tree and KD Tree for insertion, search and finding the nearest neighbours on a 2D plane

Golang Utilities for Data Analysis

A fast and efficient way to find the nearest neighbours using Kd-Tree Data structure in Unity3D.

Fortran bindings to the FLANN library for performing fast approximate nearest neighbor searches in high dimensional spaces.

Rust implementation of k-d tree to efficiently perform color quantization to predefined sets

Collision detection for 3D shapes. Axis-aligned bounding boxes (AABB).