K-means Clustering: Initialization and Image Segmentation

Covers the theory and algorithms behind image segmentation, focusing on region identification and evaluation.

Image Segmentation: K-means and Color Spaces

Explores image segmentation using K-means clustering and discusses the impact of different color spaces.

Principal Component Analysis: Dimensionality Reduction

Covers Principal Component Analysis for dimensionality reduction, exploring its applications, limitations, and importance of choosing the right components.

K-means Clustering: Lloyd's Algorithm and RGB Space

Explains K-means clustering with Lloyd's algorithm and RGB space for color segmentation.

K-Means Clustering: Basics and Applications

Introduces K-Means Clustering, a simple yet effective algorithm for grouping data points into clusters.