K-Means Clustering: Image Compression

In course

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Description

This lecture covers the implementation of the K-means algorithm for image compression, starting with clustering a 2D dataset to compressing an image by reducing the number of colors. It also includes PCA for dimensionality reduction and face image dataset analysis.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_5r8xbb5r

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Ontological neighbourhood

Computer engineering

Computer data storage: File systems

Information engineering

Machine learning: Unsupervised learning

Signal processing: Data compression

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