Patents by Inventor Suat Gedikli

Suat Gedikli 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).

  • Publication number: 20200226373
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Application
    Filed: March 27, 2020
    Publication date: July 16, 2020
    Inventors: Ryan Kottenstette, Peter Lorenzen, Suat Gedikli
  • Publication number: 20200151500
    Abstract: Systems and methods are provided for automatically detecting a change in a feature. For example, a system includes a memory and a processor configured to analyze a change associated with a feature over a period of time using a plurality of remotely sensed time series images. Upon execution, the system would receive a plurality of remotely sensed time series images, extract a feature from the plurality of remotely sensed time series images, generate at least two time series feature vectors based on the feature, where the at least two time series feature vectors correspond to the feature at two different times, create a neural network model configured to predict a change in the feature at a specified time, and determine, using the neural network model, the change in the feature at a specified time based on a change between the at least two time series feature vectors.
    Type: Application
    Filed: November 13, 2019
    Publication date: May 14, 2020
    Inventors: Ingo KOSSYK, Suat GEDIKLI
  • Patent number: 10643072
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Grant
    Filed: March 14, 2019
    Date of Patent: May 5, 2020
    Assignee: Cape Analytics, Inc.
    Inventors: Ryan Kottenstette, Peter Lorenzen, Suat Gedikli
  • Patent number: 10366288
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Grant
    Filed: March 14, 2019
    Date of Patent: July 30, 2019
    Assignee: CAPE ANALYTICS, INC.
    Inventors: Ryan Kottenstette, Peter Lorenzen, Suat Gedikli
  • Publication number: 20190213413
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Application
    Filed: March 14, 2019
    Publication date: July 11, 2019
    Inventors: Ryan KOTTENSTETTE, Peter LORENZEN, Suat GEDIKLI
  • Publication number: 20190213412
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Application
    Filed: March 14, 2019
    Publication date: July 11, 2019
    Inventors: Ryan KOTTENSTETTE, Peter LORENZEN, Suat GEDIKLI
  • Patent number: 10311302
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Grant
    Filed: August 31, 2016
    Date of Patent: June 4, 2019
    Assignee: Cape Analytics, Inc.
    Inventors: Ryan Kottenstette, Peter Lorenzen, Suat Gedikli
  • Publication number: 20180218437
    Abstract: One embodiment is directed to system for analyzing the feet of a subject, wherein the subject may position and orient his feet in a capture configuration relative to a 3-dimensional camera, and the 3-dimensional camera may be utilized to capture a plurality of images about the subject's feet from a plurality of perspectives. A point cloud may be created based upon the captured images, and extraction procedures may be conducted to create individual, or discrete, point clouds for each of the feet from the overall superset point cloud created using the 3-dimensional imaging device. The discrete point clouds may be utilized to conduct various measurements of the feet, which may be utilized in various configurations, such as for shoe fitment or manufacturing.
    Type: Application
    Filed: March 27, 2018
    Publication date: August 2, 2018
    Inventors: Radu B. Rusu, Suat Gedikli
  • Publication number: 20170076438
    Abstract: Disclosed systems and methods relate to remote sensing, deep learning, and object detection. Some embodiments relate to machine learning for object detection, which includes, for example, identifying a class of pixel in a target image and generating a label image based on a parameter set. Other embodiments relate to machine learning for geometry extraction, which includes, for example, determining heights of one or more regions in a target image and determining a geometric object property in a target image. Yet other embodiments relate to machine learning for alignment, which includes, for example, aligning images via direct or indirect estimation of transformation parameters.
    Type: Application
    Filed: August 31, 2016
    Publication date: March 16, 2017
    Inventors: Ryan KOTTENSTETTE, Peter LORENZEN, Suat GEDIKLI
  • Publication number: 20150235298
    Abstract: One embodiment is directed to system for analyzing the feet of a subject, wherein the subject may position and orient his feet in a capture configuration relative to a 3-dimensional camera, and the 3-dimensional camera may be utilized to capture a plurality of images about the subject's feet from a plurality of perspectives. A point cloud may be created based upon the captured images, and extraction procedures may be conducted to create individual, or discrete, point clouds for each of the feet from the overall superset point cloud created using the 3-dimensional imaging device. The discrete point clouds may be utilized to conduct various measurements of the feet, which may be utilized in various configurations, such as for shoe fitment or manufacturing.
    Type: Application
    Filed: April 30, 2015
    Publication date: August 20, 2015
    Applicant: Willow Garage, Inc.
    Inventors: Radu B. Rusu, Suat Gedikli