公开(公告)号：US20210342389A1

公开(公告)日：2021-11-04

申请号：US16865888

申请日：2020-05-04

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Manoj Ghuhan Arivazhagan

IPC: G06F16/583 ,  G06N20/00 ,  G06F16/532 ,  G06F16/58 ,  G06F16/54

Abstract: The disclosed techniques include at least one computer-implemented method performed by a system. The system can receive a textual query and process query features of the textual query to identify a color profile indicative of a color intent of the query. The system can identify candidate images that at least partially match the desired content and color intent of the query. The system can further order candidate images based in part on a similarity of a candidate color profile for each candidate image with the identified color profile of the query, and output image data indicative of the ordered set of candidate images.

公开(公告)号：US20230230358A1

公开(公告)日：2023-07-20

申请号：US17648482

申请日：2022-01-20

Applicant: ADOBE INC.

Inventor： Divya Kothandaraman ,  Sumit Shekhar ,  Abhilasha Sancheti ,  Manoj Ghuhan Arivazhagan ,  Tripti Shukla

IPC: G06V10/774 ,  G06V10/776 ,  G06V10/778 ,  G06V10/82

CPC classification number: G06V10/774 ,  G06V10/776 ,  G06V10/778 ,  G06V10/82

Abstract: Systems and methods for machine learning are described. The systems and methods include receiving target training data including a training image and ground truth label data for the training image, generating source network features for the training image using a source network trained on source training data, generating target network features for the training image using a target network, generating at least one attention map for training the target network based on the source network features and the target network features using a guided attention transfer network, and updating parameters of the target network based on the attention map and the ground truth label data.

公开(公告)号：US12182829B2

公开(公告)日：2024-12-31

申请号：US17849320

申请日：2022-06-24

Applicant: Adobe Inc.

Inventor： Sarthak Chakraborty ,  Sunav Choudhary ,  Atanu R. Sinha ,  Sapthotharan Krishnan Nair ,  Manoj Ghuhan Arivazhagan ,  Yuvraj ,  Atharva Anand Joshi ,  Atharv Tyagi ,  Shivi Gupta

IPC: G06Q30/0201 ,  G06N3/04 ,  G06Q30/0251

Abstract: A system includes a representation generator subsystem configured to execute a user representation model and a task prediction model to generate a user representation for a user. The user representation model receives user event sequence data comprises a sequence of user interactions with the system. The task prediction model is configured to train the user representation model. The user representation includes a vector of a predetermined size that represents the user event sequence data and is generated by applying the trained user representation model to the user event sequence data. A storage requirement of the user representation is less than a storage space requirement of the user event sequence data. The system includes a data store configured for storing the user representation in a user profile associated with the user.

公开(公告)号：US20230419339A1

公开(公告)日：2023-12-28

申请号：US17849320

申请日：2022-06-24

Applicant: Adobe Inc.

Inventor： Sarthak Chakraborty ,  Sunav Choudhary ,  Atanu R. Sinha ,  Sapthotharan Krishnan Nair ,  Manoj Ghuhan Arivazhagan ,  Yuvraj ,  Atharva Anand Joshi ,  Atharv Tyagi ,  Shivi Gupta

IPC: G06Q30/02 ,  G06N3/04

CPC classification number: G06Q30/0201 ,  G06N3/04 ,  G06Q30/0269 ,  G06Q30/0255

Abstract: A system includes a representation generator subsystem configured to execute a user representation model and a task prediction model to generate a user representation for a user. The user representation model receives user event sequence data comprises a sequence of user interactions with the system. The task prediction model is configured to train the user representation model. The user representation includes a vector of a predetermined size that represents the user event sequence data and is generated by applying the trained user representation model to the user event sequence data. A storage requirement of the user representation is less than a storage space requirement of the user event sequence data. The system includes a data store configured for storing the user representation in a user profile associated with the user.

公开(公告)号：US20220269935A1

公开(公告)日：2022-08-25

申请号：US17182734

申请日：2021-02-23

Applicant: Adobe Inc.

Inventor： Manoj Ghuhan Arivazhagan ,  Samanway Sadhu ,  Sahil Dhull ,  Niyati Himanshu Chhaya ,  Munipalle Sai Nikhila

IPC: G06N3/08 ,  G06N3/04 ,  H04L29/08

Abstract: A digital experience personalization system monitors user interaction with content during a current browsing session. The digital experience personalization system generates user interaction information, which includes a description of the content with which the user interacted during the current browsing session, an indication of how long the user interacted with the content, and an indication of the type of the user interaction (e.g., clicking on content, scrolling through content, hovering over content). The digital experience personalization system employs a cognitive style prediction module to analyze the user interaction information and generate a prediction of a cognitive style the user prefers for consuming content. Subsequent content (e.g., during the current browsing session) is personalized to the user in accordance with the predicted cognitive style of the user.