公开(公告)号：US20220351513A1

公开(公告)日：2022-11-03

申请号：US17865076

申请日：2022-07-14

Applicant: Adobe Inc.

Inventor： Jayant Kumar ,  Vera Lychagina ,  Tarun Vashisth ,  Sudhakar Pandey ,  Sharad Mangalick ,  Rohith Mohan Dodle ,  Peter Baust ,  Mina Doroudi ,  Kerem Turgutlu ,  Kannan Iyer ,  Gaurav Kukal ,  Archit Kalra ,  Amine Ben Khalifa

IPC: G06V20/00 ,  G06K9/62 ,  G06F16/53 ,  G06N3/08

Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.

公开(公告)号：US11710312B2

公开(公告)日：2023-07-25

申请号：US17865076

申请日：2022-07-14

Applicant: Adobe Inc.

Inventor： Jayant Kumar ,  Vera Lychagina ,  Tarun Vashisth ,  Sudhakar Pandey ,  Sharad Mangalick ,  Rohith Mohan Dodle ,  Peter Baust ,  Mina Doroudi ,  Kerem Turgutlu ,  Kannan Iyer ,  Gaurav Kukal ,  Archit Kalra ,  Amine Ben Khalifa

IPC: G06V20/00 ,  G06F16/53 ,  G06N3/08 ,  G06F18/23 ,  G06F18/214

CPC classification number: G06V20/35 ,  G06F16/53 ,  G06F18/214 ,  G06F18/23 ,  G06N3/08

Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.

公开(公告)号：US20200065425A1

公开(公告)日：2020-02-27

申请号：US16107769

申请日：2018-08-21

Applicant: Adobe Inc.

Inventor： Charles Menguy ,  Sudhakar Pandey ,  Roshan Singh ,  Ravi Prakash Singh ,  David Meier Weinstein ,  Ankush Sharma

IPC: G06F17/30 ,  H04L29/08

Abstract: Systems and techniques for delivery of contextual interest from interaction information are described that process user interactions with digital content to generate user interest scores for various topics. A contextual user interest system uses user interaction data to identify and contextualize content, and assigns propensity scores to the contextualized content. By dynamically contextualizing pages of content, the contextual user interest system may adapt to changes in the content and provide more accurate and robust information over time, which is not possible using conventional techniques. The contextualized pages of content are used to assign user interest scores across a number of topics to users who have visited the pages of content, and the user interest scores are normalized in a manner that allows a user's degree of interest in a topic to be compared to that of another user.

公开(公告)号：US11468674B2

公开(公告)日：2022-10-11

申请号：US16995869

申请日：2020-08-18

Applicant: Adobe Inc.

Inventor： Jayant Kumar ,  Vera Lychagina ,  Tarun Vashisth ,  Sudhakar Pandey ,  Sharad Mangalick ,  Rohith Mohan Dodle ,  Peter Baust ,  Mina Doroudi ,  Kerem Turgutlu ,  Kannan Iyer ,  Gaurav Kukal ,  Archit Kalra ,  Amine Ben Khalifa

IPC: G06V20/00 ,  G06K9/62 ,  G06F16/53 ,  G06N3/08

Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method includes training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; and determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images.

公开(公告)号：US10997264B2

公开(公告)日：2021-05-04

申请号：US16107769

申请日：2018-08-21

Applicant: Adobe Inc.

Inventor： Charles Menguy ,  Sudhakar Pandey ,  Roshan Singh ,  Ravi Prakash Singh ,  David Meier Weinstein ,  Ankush Sharma

IPC: G06F17/20 ,  G06F16/957 ,  H04L29/08 ,  G06F16/31 ,  G06F16/9535 ,  G06F16/955

Abstract: Systems and techniques for delivery of contextual interest from interaction information are described that process user interactions with digital content to generate user interest scores for various topics. A contextual user interest system uses user interaction data to identify and contextualize content, and assigns propensity scores to the contextualized content. By dynamically contextualizing pages of content, the contextual user interest system may adapt to changes in the content and provide more accurate and robust information over time, which is not possible using conventional techniques. The contextualized pages of content are used to assign user interest scores across a number of topics to users who have visited the pages of content, and the user interest scores are normalized in a manner that allows a user's degree of interest in a topic to be compared to that of another user.