A parallelised implementation of the K-means clustering algorithm using C Pthreads and separately using OpenMP specification for C
-
Updated
Feb 12, 2019 - C
A parallelised implementation of the K-means clustering algorithm using C Pthreads and separately using OpenMP specification for C
An award-winning Adobe After Effects plugin that creates Islamic star pattern-style animations using the Hankin's polygons-in-contact algorithm. Colors for animations are generated from an Image dataset through k-means clustering.
An implementation of the K Means Clustering ML Algorithm in C language using OpenMP
Implementation in C of a custom k-means for clouds detection in satellite images.
2019~2020学年第2学期《并行程序设计》课程设计
Kmeans clustering using c , openmp , cuda and mpi program
A k-means algorithm implementation to c language.
Cloud detection in optical satellite images
Parallellization of the Kmeans algorithm with OpenMP
The repository includes the code for serial and parallel K Means using CUDA and MPI for Image Compression.
Implementation of K-Means clustering algorithm from scratch. Parallelization of clustering algorithm across multiple nodes using OpenMP and MPI to reduce clustering time on a huge dataset. Also performance analysis of multiple approaches used and their comparison.
Parallelized versions of popular Machine Learning algorithms, written in C using (mostly) the OpenMP API.
Approximative Linear t-SNE using k-Means. Master thesis at the research group Data Mining, University of Vienna, Spring 2021.
Image Segmentation using K-means
K-Means Clustering Algorithm visualized using OpenGL with an extensible interface.
Parallel k-means implementation using OpenMP
Algos de machine learning
Código desenvolvido como parte da avaliação da disciplina Algoritmos e Programação de Computadores (113476) com o professor Vinícius Ruela Pereira Borges do departamento de Ciência da computação da Universidade de Brasília no primeiro semestre de 2018, desenvolvido pelo estudante Felipe Luís Pinheiro.
Add a description, image, and links to the kmeans-clustering topic page so that developers can more easily learn about it.
To associate your repository with the kmeans-clustering topic, visit your repo's landing page and select "manage topics."