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    <title>'Neural Net Object Orientation' Thread RSS Feed</title>
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    <pubDate>Sat, 25 May 2013 15:16:57 -0700</pubDate>
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      <title>Neural Net Object Orientation</title>
      <link>http://www.programmersheaven.com/mb/Algorithms/170730/170730/neural-net-object-orientation/</link>
      <description>I have to write a neural net for my uni course to recognise peoples faces. The pictures may be at different orientations to those given as training data. &lt;br /&gt;
   Does anyone any ideas on what network would be best (I was thinking back propogation) and algorithms to preprocess the image to orientate it.&lt;br /&gt;
&lt;br /&gt;
I inted to scale the pricture so that the actual face is always the same percentage of the whole image before feeding the pixel values into the net. &lt;br /&gt;
&lt;br /&gt;
The only way I can think of to find the orientation is to rotate the input points one unit at a time, monitoring the output to find the most likely image. This would seem to have a very large processing overhead though. Any thoughts?&lt;br /&gt;
&lt;br /&gt;
Cheers guys&lt;br /&gt;
&lt;br /&gt;
Tom&lt;br /&gt;</description>
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      <pubDate>Thu, 13 Feb 2003 07:49:37 -0700</pubDate>
      <category>Algorithms</category>
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