Patents by Inventor Fred Aye Zaw, JR.

Fred Aye Zaw, JR. 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).

  • GENERATING PERSONALIZED BANNER IMAGES USING MACHINE LEARNING
    Publication number: 20230076209
    Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.
    Type: Application
    Filed: November 14, 2022
    Publication date: March 9, 2023
    Inventors: Shuai Zheng, Mohammadhadi Kiapour, Nandini Ramakrishnan, Christophe Boudet, JR., Fred Aye Zaw, JR.
  • Generating personalized banner images using machine learning
    Patent number: 11507984
    Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.
    Type: Grant
    Filed: November 30, 2020
    Date of Patent: November 22, 2022
    Assignee: eBay Inc.
    Inventors: Shuai Zheng, Mohammadhadi Kiapour, Nandini Ramakrishnan, Christophe Boudet, Fred Aye Zaw, Jr.
  • GENERATING PERSONALIZED BANNER IMAGES USING MACHINE LEARNING
    Publication number: 20210103957
    Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.
    Type: Application
    Filed: November 30, 2020
    Publication date: April 8, 2021
    Inventors: Shuai Zheng, Mohammadhadi Kiapour, Nandini Ramakrishnan, Christophe Boudet, Fred Aye Zaw, JR.
  • Generating personalized banner images using machine learning
    Patent number: 10885558
    Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.
    Type: Grant
    Filed: October 9, 2018
    Date of Patent: January 5, 2021
    Assignee: eBay Inc.
    Inventors: Shuai Zheng, Mohammadhadi Kiapour, Nandini Ramakrishnan, Christophe Boudet, Fred Aye Zaw, Jr.
  • GENERATING PERSONALIZED BANNER IMAGES USING MACHINE LEARNING
    Publication number: 20200111134
    Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.
    Type: Application
    Filed: October 9, 2018
    Publication date: April 9, 2020
    Inventors: Shuai Zheng, Mohammadhadi Kiapour, Nandini Ramakrishnan, Christophe Boudet, Fred Aye Zaw, JR.