Patents by Inventor Murilo Maeda

Murilo Maeda 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: 11816834
    Abstract: Various embodiments are disclosed for a machine learning system for automatic genotype selection and performance evaluation using multi-source and spatiotemporal remote sensing data collected from an unmanned aerial system (UAS). A computing device may be configured to access images of a field having a first genotype and a second genotype of at least one crop or plant planted therein. The computing device may apply an image processing routine to the images to analyze the images of the field and determine characteristics of the first genotype and the second genotype of the at least one crop or plant planted in the field. The computing device may then apply a machine learning routine to forecast a first estimated yield of the first genotype and a second estimated yield of the second genotype using the identified characteristics of the first genotype and the second genotype.
    Type: Grant
    Filed: January 6, 2021
    Date of Patent: November 14, 2023
    Assignee: The Texas A&M University System
    Inventors: Jinha Jung, Juan Landivar, Murilo Maeda, Akash Ashapure
  • Publication number: 20210209747
    Abstract: Various embodiments are disclosed for a machine learning system for automatic genotype selection and performance evaluation using multi-source and spatiotemporal remote sensing data collected from an unmanned aerial system (UAS). A computing device may be configured to access images of a field having a first genotype and a second genotype of at least one crop or plant planted therein. The computing device may apply an image processing routine to the images to analyze the images of the field and determine characteristics of the first genotype and the second genotype of the at least one crop or plant planted in the field. The computing device may then apply a machine learning routine to forecast a first estimated yield of the first genotype and a second estimated yield of the second genotype using the identified characteristics of the first genotype and the second genotype.
    Type: Application
    Filed: January 6, 2021
    Publication date: July 8, 2021
    Applicant: The Texas A&M University System
    Inventors: Jinha Jung, Juan Landivar, Murilo Maeda, Akash Ashapure