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TRAINING AN IMAGE PROCESSING NEURAL NETWORK WITHOUT HUMAN SELECTION OF FEATURES

  • US 20130266214A1
  • Filed: 04/05/2013
  • Published: 10/10/2013
  • Est. Priority Date: 04/06/2012
  • Status: Active Grant
First Claim
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1. A method for training an image processing neural network without human selection of features, the method comprising:

  • providing a training set comprising images labeled with two or more classifications;

    providing an image processing toolbox comprising a plurality of image transforms;

    generating a random set of feature extraction pipelines, each feature extraction pipeline comprising a sequence of image transforms randomly selected from the image processing toolbox and randomly selected control parameters associated with the sequence of image transforms;

    coupling a first stage classifier to an output of each feature extraction pipeline; and

    executing a genetic algorithm to conduct genetic modification of each feature extraction pipeline and train each first stage classifier on the training set.

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