Fuzzing with the generated argument
-
Updated
Jan 6, 2023 - C
Fuzzing with the generated argument
Parallel implementation of K-means Clustering algorithm using OpenMp in C
Project for the Neural Networks course @cse.uoi.gr
Various MPI and PThreads optimizations for boosting performances of k-means clustering algorithm
The text message is encrypted using 128 bit key AES encryption. Then steganography is performed using k-means clustering and LSB technique
Genetic diseases analyzation using K-means clustering and OpenMP.
Machine learning methods and image processing were utilized to determine whether a surface contains a deformity. Through the development of a C++ program to generate surface deformities given image length, width, maximum deformity radius, and sample size as the training set, we utilize machine learning classifiers, namely Convolution Neural Netw…
Clustering algorithm with other functions (Laplacian Norm, Jacobi algorithm - Eigenvalues and Eigenvectors extractor, etc)
C Implementation of the K-MEANS algorithm. The code has been parallelized using the OpenMP API.
This program implements the K-means clustering algorithm using OpenMP APIs. The K-means algorithm is a popular method of vector quantization that aims to partition n observations into k clusters. Each observation is assigned to the cluster with the nearest mean, serving as a prototype of the cluster.
A simple multithread implementation of the n-dimensional K-means algorithm developed in C using OpenMP.
K-Mean clustering algorithm implementation in C++ with GLFW3 OpenGL
Proyecto de genética utilizando OpenMP y K-means clustering
Proyecto para arquitectura de computadores: Trata de una simplificación de una aplicación real, del ámbito del (NLP) Natural Language Processing y (ML) Machine Learning al que se le van a aplicar tecnicas de paralelizacion mediante la libreria de OpenMP para encontrar la version mas eficiente.
A simple k-means algorithm where the centroids are already defined.
Image Compression using K-Means Algorithm
A k-means algorithm implementation to c language.
Computer vision exercises
A project that involved C programming. Where we made use of parallel implementations of OpenMPI and Cuda. We compared the performance of these two and attempted to perform K Means and Fuzzy C Means clustering on synthetic data.
Add a description, image, and links to the k-means-clustering topic page so that developers can more easily learn about it.
To associate your repository with the k-means-clustering topic, visit your repo's landing page and select "manage topics."