Patents by Inventor Corey Pittman

Corey Pittman 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).

  • Synthetic data generation of time series data
    Patent number: 10133949
    Abstract: A method of generating synthetic data from time series data, such as from handwritten characters, words, sentences, mathematics, and sketches that are drawn with a stylus on an interactive display or with a finger on a touch device. This computationally efficient method is able to generate realistic variations of a given sample. In a handwriting or sketch recognition context, synthetic data is generated from real data in order to train recognizers and thus improve recognition accuracy when only a limited number of samples are available. Similarly, synthetic data can also be used to test and validate such recognizers. Also discussed is a dynamic time warping based approach for both segmented and continuous data that is designed to be a robust, go-to method for gesture recognition across a variety of modalities using only limited training samples.
    Type: Grant
    Filed: July 17, 2017
    Date of Patent: November 20, 2018
    Assignee: University of Central Florida Research Foundation, Inc.
    Inventors: Eugene M. Taranta, II, Mehran Maghoumi, Corey Pittman, Joseph J. LaViola, Jr.
  • SYNTHETIC DATA GENERATION OF TIME SERIES DATA
    Publication number: 20180018533
    Abstract: A method of generating synthetic data from time series data, such as from handwritten characters, words, sentences, mathematics, and sketches that are drawn with a stylus on an interactive display or with a finger on a touch device. This computationally efficient method is able to generate realistic variations of a given sample. In a handwriting or sketch recognition context, synthetic data is generated from real data in order to train recognizers and thus improve recognition accuracy when only a limited number of samples are available. Similarly, synthetic data can also be used to test and validate such recognizers. Also discussed is a dynamic time warping based approach for both segmented and continuous data that is designed to be a robust, go-to method for gesture recognition across a variety of modalities using only limited training samples.
    Type: Application
    Filed: July 17, 2017
    Publication date: January 18, 2018
    Inventors: Eugene M. Taranta, II, Mehran Maghoumi, Corey Pittman, Joseph J. LaViola, Jr.