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	<title>Shyam Guthikonda &#187; ui</title>
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		<title>Kohonen Self-Organizing Map Demos</title>
		<link>http://www.shy.am/2005/12/kohonen-self-organizing-map-demos/</link>
		<comments>http://www.shy.am/2005/12/kohonen-self-organizing-map-demos/#comments</comments>
		<pubDate>Mon, 05 Dec 2005 09:43:36 +0000</pubDate>
		<dc:creator>shyam</dc:creator>
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		<description><![CDATA[In artificial intelligence, SOMs, or Self-Organizing Maps, are a type of neural network. They can be used to &#8216;teach&#8217; a computer to recognize various attributes. This project deals with two demos: SOM_Color and SOM_Image. Both are written in C#. SOM_Color is a color recognition program. A grid of nodes is initialized with random colors. The [...]]]></description>
			<content:encoded><![CDATA[<p>In artificial intelligence, SOMs, or Self-Organizing Maps, are a type of neural network. They can be used to &#8216;teach&#8217; a computer to recognize various attributes. This project deals with two demos: SOM_Color and SOM_Image. Both are written in C#.</p>
<p>SOM_Color is a color recognition program. A grid of nodes is initialized with random colors. The application learns how the colors are related to each other, and will sort the colors so that like-colors end up near each other. Color &#8220;similarity&#8221; is defined by their respective RGB color vector Euclidean distance.</p>
<p>SOM_Image is an image recognition program. A database of images is presented to the application (Madden NFL &#8217;06 images are provided with the download). The program will group similar images near each other. Two classifications are used for this similarity calculation: a histogram of lights/darks and colors. This application works surprisingly well.</p>
<p>There is also a <a href="http://www.shy.am/wp-content/uploads/2009/01/kohonen-self-organizing-maps-shyam-guthikonda.pdf">paper</a> that goes along with this project, to better explain the utilized techniques.</p>

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<p><strong>Download: </strong><a href="http://www.shy.am/projects/SOM.zip">source</a></p>
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