Loading repository data…
nsr789 / repository
This GitHub repository contains a MATLAB implementation of the K-Means clustering algorithm from scratch, along with an analysis of finding the optimal K-value using the elbow method. K-Means is a widely used unsupervised machine learning algorithm for clustering data points into distinct groups based on their similarity.
A transparent discovery signal based on current public GitHub metadata.
This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
README preview is not available for this repository.
Selected from shared topics, language and repository description—not editorial ratings.
mathworks /
This repository contains a regular expression based language grammar for MATLAB to be used by GitHub Linguist for highlighting MATLAB code on GitHub
52/100 healthn-jokic /
This GitHub repository implements two Model Predictive Control (MPC) approaches for active front steering systems in autonomous vehicles. The methods are inspired by groundbreaking scientific papers. The project utilizes MATLAB and Simulink, requiring
66/100 healthmathworks-robotics /
This GitHub repository contains MATLAB and Simulink utilities and templates to get started developing algorithms for the RoboCup Virtual Robot Manipulation Challenge. The templates include how to control the simulated robot in Gazebo using ROS and how to obtain data from the available robot sensors to be used in perception algorithms.
CisottoGiulia /
This repository contains a set of Matlab scripts to process EEG and EMG signals (feature extraction, spectral analysis, ...).
69/100 healthlinh-gist /
This repository includes Python implementations adapted from Matlab, originally developed by Prof. Ba-Tuong Vo. The original Matlab codes can be found at Prof. Vo's website (https://ba-tuong.vo-au.com/codes.html) or on GitHub (https://github.com/nguyenvanhoa89/tracking/tree/master/Vo_Codes).
78/100 healthalessandroferrari /
Python-caffe simplified implementation of the R-CNN object detection method. I have taken as a starting point the caffe ipython-notebook available at http://nbviewer.ipython.org/github/BVLC/caffe/blob/master/examples/detection.ipynb . The tutorial requires the use of matlab code for calculating selective search bounding boxes. This make it hard to use and slow. Thus, I have implemented bounding boxes proposal with a pythonized BING that I have implemented in another repository. I have also changed the interaction with the script so that the result is a nicer demo.
34/100 health