Patents by Inventor Keilan Scholten

Keilan Scholten 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).

  • Yield forecasting using crop specific features and growth stages
    Patent number: 11321941
    Abstract: A method for predicting crop yield of an agricultural field may include steps of applying a pre-season model to provide a pre-season model crop yield prediction, applying an in-season model to provide an in-season model crop yield prediction, applying a statistical imagery model to provide a statistical imagery model crop yield prediction, applying a histogram-based image model to provide a histogram-based image model crop yield prediction, applying crop-specific models to provide at least one crop-specific model crop yield prediction, and combining at a computing system crop yield predictions from a plurality of models within a set comprising the pre-season model, the in-season model, the statistical imagery model, the histogram-based image model, and the crop-specific models, to produce a final crop yield prediction.
    Type: Grant
    Filed: April 10, 2020
    Date of Patent: May 3, 2022
    Assignee: Farmers Edge Inc.
    Inventors: Jacob Walker Bengtson, Chad Richard Bryant, Changchi Xian, Charles Cuell, Keilan Scholten, Fatema Tuz Zohra
  • YIELD FORECASTING USING CROP SPECIFIC FEATURES AND GROWTH STAGES
    Publication number: 20200342226
    Abstract: A method for predicting crop yield of an agricultural field may include steps of applying a pre-season model to provide a pre-season model crop yield prediction, applying an in-season model to provide an in-season model crop yield prediction, applying a statistical imagery model to provide a statistical imagery model crop yield prediction, applying a histogram-based image model to provide a histogram-based image model crop yield prediction, applying crop-specific models to provide at least one crop-specific model crop yield prediction, and combining at a computing system crop yield predictions from a plurality of models within a set comprising the pre-season model, the in-season model, the statistical imagery model, the histogram-based image model, and the crop-specific models, to produce a final crop yield prediction.
    Type: Application
    Filed: April 10, 2020
    Publication date: October 29, 2020
    Applicant: Farmers Edge Inc.
    Inventors: Jacob Walker Bengtson, Chad Richard Bryant, Changchi Xian, Charles Cuell, Keilan Scholten, Fatema Tuz Zohra