Patents by Inventor Christopher A. Bischke

Christopher A. Bischke has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Automatic segmentation of data derived from learned features of a predictive statistical model
    Patent number: 10832149
    Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions executed by the processor to specifically configure the processor to implement a statistical model tool for providing insight into decision making. The statistical model tool applies the statistical model to an input image to generate an original classification probability. An image modification component executing within the statistical model tool iterative modifies each portion of the input image to generate a modified image. The statistical model tool applies the statistical model to the modified image to generate a new classification probability for each portion of the input image. A compare component executing in the statistical model tool compares each new classification probability to the original classification probability to generate a respective probability distance.
    Type: Grant
    Filed: December 10, 2018
    Date of Patent: November 10, 2020
    Assignee: International Business Machines Corporation
    Inventors: Michael C. Mudie, Christopher A. Bischke, Abhijit Tomar
  • Automatic segmentation of data derived from learned features of a predictive statistical model
    Patent number: 10650315
    Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions executed by the processor to specifically configure the processor to implement a statistical model tool for providing insight into decision making. The statistical model tool applies the statistical model to an input image to generate an original classification probability. An image modification component executing within the statistical model tool iterative modifies each portion of the input image to generate a modified image. The statistical model tool applies the statistical model to the modified image to generate a new classification probability for each portion of the input image. A compare component executing in the statistical model tool compares each new classification probability to the original classification probability to generate a respective probability distance.
    Type: Grant
    Filed: June 14, 2018
    Date of Patent: May 12, 2020
    Assignee: International Business Machines Corporation
    Inventors: Michael C. Mudie, Christopher A. Bischke, Abhijit Tomar
  • Automatic Segmentation of Data Derived from Learned Features of a Predictive Statistical Model
    Publication number: 20190385076
    Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions executed by the processor to specifically configure the processor to implement a statistical model tool for providing insight into decision making. The statistical model tool applies the statistical model to an input image to generate an original classification probability. An image modification component executing within the statistical model tool iterative modifies each portion of the input image to generate a modified image. The statistical model tool applies the statistical model to the modified image to generate a new classification probability for each portion of the input image. A compare component executing in the statistical model tool compares each new classification probability to the original classification probability to generate a respective probability distance.
    Type: Application
    Filed: December 10, 2018
    Publication date: December 19, 2019
    Inventors: Michael C. Mudie, Christopher A. Bischke, Abhijit Tomar
  • Automatic Segmentation of Data Derived from Learned Features of a Predictive Statistical Model
    Publication number: 20190385075
    Abstract: A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions executed by the processor to specifically configure the processor to implement a statistical model tool for providing insight into decision making. The statistical model tool applies the statistical model to an input image to generate an original classification probability. An image modification component executing within the statistical model tool iterative modifies each portion of the input image to generate a modified image. The statistical model tool applies the statistical model to the modified image to generate a new classification probability for each portion of the input image. A compare component executing in the statistical model tool compares each new classification probability to the original classification probability to generate a respective probability distance.
    Type: Application
    Filed: June 14, 2018
    Publication date: December 19, 2019
    Inventors: Michael C. Mudie, Christopher A. Bischke, Abhijit Tomar