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Self-Organizing Maps for Texture Classification by أيمن عبد البر is a document available to read on EtoBox.

What is Self-Organizing Maps for Texture Classification about?

This document summarizes a study that used self-organizing maps (SOMs) for unsupervised texture classification. The study used a dataset of 335 texture images from 7 classes. Features were extracted from the images including co-occurrence matrices, Laws

Author

أيمن عبد البر

Language

EN