A lean C++ library for working with point cloud data
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Updated
Aug 15, 2023 - C++
A lean C++ library for working with point cloud data
An interactive approach to understanding Machine Learning using scikit-learn
Cool Vision projects
Official code for "Mean Shift for Self-Supervised Learning"
Implementation of feature engineering from Feature engineering strategies for credit card fraud
Algorithm for tracking an object based on the mean shift algorithm
Mean-shift clustering in Python in 100 lines
Utilize Mean-Shift to generate initial centroids for K-Means
GPU accelerated Faster Mean-shift for cosine embedding clustering
Offline and online (i.e., real-time) annotated clustering methods for text data.
Machine learning Beginning using python
사용자가 코치의 도움없이 여러 훈련을 개인적으로 할 수 있도록 도와주는 축구 어플리케이션입니다. It is a soccer-practice-application that helps the user to do various training personally without the help of a coach.
GPU accelerated K-Means and Mean Shift clustering in Tensorflow.
Real Time Tracking based in Mean Shift framework using LIBAV and SDL libraries (Without using OpenCV Library).
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"
Image processing and vision based assignments completed in computer vision course
CS663 - Digital Image Processing Programming Assignments
This module covers the concept of clustering in machine learning. It explains three of the most common clustering algorithms, with a hands-on approximation to solve a real-life data problem. The three clustering algorithms covered are k-means, mean-shift and DBSCAN algorithms.
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