IEEE

Optimisation Research on K-Means Clustering Algorithm Based on Principal Component Analysis and Percentile Improvement

Abstract: The traditional K-means algorithm often leads to unstable clustering quality due to the randomness of the initial clustering center selection and tends to fall into suboptimal solutions when ...
Hosted on MSN

What AI algorithms did to streaming and what it means for broadcast TV

AI content creation has exploded, creating a wave of auto-generated videos, scripts, and shows that compete with traditional programming. Live TV still holds power in news and sports, but audiences ...
GitHub

k-means-clustering

cellUview is alternative software that runs on an OpenFlexure 3D-printed microscope. Images are enhanced in real-time by changing exposure, contrast, edge enhancement, dilation, contrast and k-means ...
IEEE

A Topological-Indicators-Based k-Means Clustering Algorithm and Its Application in Time Series Data: A Case Study on Sea Level Variability in Peninsular Malaysia

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...