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Snow classifier context window reduction using class t-scores and mean differences

  • US 9,195,908 B2
  • Filed: 05/22/2013
  • Issued: 11/24/2015
  • Est. Priority Date: 05/22/2013
  • Status: Active Grant
First Claim
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1. A method for determining important locations of a classifier, said method comprising:

  • calculating a mean deviation and a standard deviation of every pixel location in a classifier with respect to positive and negative samples associated with said classifier;

    ranking an importance of all pixel locations calculated with respect to said classifier based on a combination of t-scores and mean differences; and

    selecting a number of said locations to achieve a detection rate for said classifier for a particular application in order to determine which locations of said classifier are involved in discrimination between class objects and non-class objects.

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