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Optimizing multi-class image classification using patch features

  • US 10,013,637 B2
  • Filed: 01/22/2015
  • Issued: 07/03/2018
  • Est. Priority Date: 01/22/2015
  • Status: Active Grant
First Claim
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1. A computer storage media encoded with instructions that, when executed by a processor, configure a computer to perform acts comprising:

  • accessing a plurality of weakly supervised images;

    extracting one or more patches from individual weakly supervised images of the plurality of weakly supervised images;

    extracting patch-based features from the one or more patches;

    arranging individual patches into a plurality of clusters based at least in part on the patch-based features;

    removing at least some of the individual patches from at least one cluster of the plurality of clusters based at least in part on similarity values representative of a similarity between ones of the individual patches arranged in the at least one cluster; and

    training a classifier for at least one label of a plurality of labels based at least in part on the plurality of clusters, comprising;

    extracting new patch-based features from remaining individual patches of the at least one cluster; and

    training the classifier based at least in part on the new patch-based features.

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