Training an auto-encoder on a single class

  • US 10,607,135 B2
  • Filed: 12/27/2017
  • Issued: 03/31/2020
  • Est. Priority Date: 10/19/2017
  • Status: Active Grant
First Claim
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1. A machine learning system, comprising:

  • a memory that stores computer executable components;

    a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise;

    an auto-encoder component that trains an auto-encoder based on first data associated with a first class to generate a trained auto-encoder;

    a multiplier component that applies, using a multiplier, gain data indicative of a gain value to second data associated with the first class and third data associated with a second class to generate enhanced input data that represents a differentiation between the second data associated with the first class and the third data associated with the second class, wherein an input enhancer comprises the trained auto-encoder and the multiplier;

    a convolutional neural network component that trains a convolutional neural network based on the enhanced input data to generate a trained convolutional neural network; and

    a classification component that classifies the first class and the second class based on the input enhancer and the trained convolutional neural network.

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