Patents by Inventor Alan Chad DeChant

Alan Chad DeChant 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).

  • Methods and systems for pattern characteristic detection
    Patent number: 10747999
    Abstract: Disclosed are devices, systems, apparatus, methods, products, and other implementations, including a method to detect pattern characteristics in target specimens that includes acquiring sensor data for the target specimens, dividing the acquired sensor data into a plurality of data segments, and generating, by multiple neural networks that each receives the plurality of data segments, multiple respective output matrices, with each data element of the multiple respective output matrices being representative of a probability that corresponding sensor data of a respective one of the plurality of data segments includes a pattern characteristic in the target specimens. The method further includes determining by another neural network, based on the multiple respective output matrices generated by the multiple neural networks, a presence of the pattern characteristic in the target specimens.
    Type: Grant
    Filed: October 16, 2018
    Date of Patent: August 18, 2020
    Assignees: The Trustees of Columbia University in the City of New York, Cornell University
    Inventors: Alan Chad DeChant, Hod Lipson, Rebecca J. Nelson, Michael A. Gore, Tyr Wiesner-Hanks, Ethan Stewart, Jason Yosinski, Siyuan Chen
  • METHODS AND SYSTEMS FOR PATTERN CHARACTERISTIC DETECTION
    Publication number: 20190114481
    Abstract: Disclosed are devices, systems, apparatus, methods, products, and other implementations, including a method to detect pattern characteristics in target specimens that includes acquiring sensor data for the target specimens, dividing the acquired sensor data into a plurality of data segments, and generating, by multiple neural networks that each receives the plurality of data segments, multiple respective output matrices, with each data element of the multiple respective output matrices being representative of a probability that corresponding sensor data of a respective one of the plurality of data segments includes a pattern characteristic in the target specimens. The method further includes determining by another neural network, based on the multiple respective output matrices generated by the multiple neural networks, a presence of the pattern characteristic in the target specimens.
    Type: Application
    Filed: October 16, 2018
    Publication date: April 18, 2019
    Inventors: Alan Chad DeChant, Hod Lipson, Rebecca J. Nelson, Michael A. Gore, Tyr Wiesner-Hanks, Ethan Stewart, Jason Yosinski, Siyuan Chen