AZoM on MSN

Imaging silicon defects using Raman and PL multivariate imaging

PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
The New York Times

Calley Means, a Kennedy Adviser, Has Left the White House

Mr. Means quietly departed his federal role about a month ago. His sister has been nominated for surgeon general. By Benjamin Mueller Calley Means, an influential adviser to Health Secretary Robert F.
IEEE

Research on Improved k-Means Clustering Algorithm Based on Density-Weighted Canopy

Abstract: This paper proposes an improved K-means clustering algorithm based on density-weighted Canopy to address the efficiency bottlenecks and clustering accuracy issues commonly encountered by ...
Scientific Research Publishing

Ng, H.P., Ong, S.H., Foong, K.W.C., Goh, P.S. and Nowinski, W.L. Medical Image Segmentation Using K-Means Clustering and Improved Watershed Algorithm. 2006 IEEE Southwest ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
Scientific Research Publishing

Applying K-Means Clustering and Fuzzy C-Means Clustering in Vehicle Crashes ()

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...
GitHub

k-means-clustering

This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...