Patents by Inventor Mark Peot

Mark Peot 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).

  • Patent number: 8758018
    Abstract: EEG-based acceleration of second language learning is accomplished by measuring via single-trial EEG a learner's cognitive response to the presentation (visual or auditory) of language learning materials and updating a user model of latent traits related to language-learning skills in accordance with the cognitive response. The user model is suitably updated with each trial, each trial being triggered by learner fixation on a portion of visual materials and/or a next phoneme in auditory materials. Additional discrimination may be achieved through the use of saccades or fixation duration features.
    Type: Grant
    Filed: December 31, 2009
    Date of Patent: June 24, 2014
    Assignee: Teledyne Scientific & Imaging, LLC
    Inventors: Mark Peot, Mario Aguilar, Aaron T. Hawkins
  • Publication number: 20110159467
    Abstract: EEG-based acceleration of second language learning is accomplished by measuring via single-trial EEG a learner's cognitive response to the presentation (visual or auditory) of language learning materials and updating a user model of latent traits related to language-learning skills in accordance with the cognitive response. The user model is suitably updated with each trial, each trial being triggered by learner fixation on a portion of visual materials and/or a next phoneme in auditory materials. Additional discrimination may be achieved through the use of saccades or fixation duration features.
    Type: Application
    Filed: December 31, 2009
    Publication date: June 30, 2011
    Inventors: MARK PEOT, Mario Aguilar, Aaron T. Hawkins
  • Publication number: 20070130095
    Abstract: Bayesian super-resolution techniques fuse multiple low resolution images (possibly from multiple bands) to infer a higher resolution image. The super-resolution and fusion concepts are portable to a wide variety of sensors and environmental models. The procedure is model-based inference of super-resolved information. In this approach, both the point spread function of the sub-sampling process and the multi-frame registration parameters are optimized simultaneously in order to infer an optimal estimate of the super-resolved imagery. The procedure involves a significant number of improvements, among them, more accurate likelihood estimates and a more accurate, efficient, and stable optimization procedure.
    Type: Application
    Filed: September 30, 2005
    Publication date: June 7, 2007
    Inventors: Mark Peot, Mario Aguilar