Patents by Inventor Stephen Wistar

Stephen Wistar 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: 10019658
    Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.
    Type: Grant
    Filed: August 9, 2017
    Date of Patent: July 10, 2018
    Assignee: THE PENN STATE UNIVERSITY
    Inventors: James Z. Wang, Yu Zhang, Stephen Wistar, Michael A. Steinberg, Jia Li
  • Publication number: 20180018543
    Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.
    Type: Application
    Filed: August 9, 2017
    Publication date: January 18, 2018
    Inventors: James Z. Wang, Yu Zhang, Stephen Wistar, Michael A. Steinberg, Jia Li
  • Patent number: 9760805
    Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.
    Type: Grant
    Filed: October 9, 2015
    Date of Patent: September 12, 2017
    Assignee: The Penn State Research Foundation
    Inventors: James Z. Wang, Yu Zhang, Stephen Wistar, Michael A. Steinberg, Jia Li
  • Publication number: 20160104059
    Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.
    Type: Application
    Filed: October 9, 2015
    Publication date: April 14, 2016
    Inventors: James Z. Wang, Yu Zhang, Stephen Wistar, Michael A. Steinberg, Jia Li