公开(公告)号：US20190147305A1

公开(公告)日：2019-05-16

申请号：US15812695

申请日：2017-11-14

Applicant: Adobe Inc.

Inventor： Xin Lu ,  Zejun Huang ,  Jen-Chan Jeff Chien

IPC: G06K9/72 ,  G06K9/62 ,  G06K9/00 ,  H04N1/21 ,  G06F17/30

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media that automatically select an image from a plurality of images based on the multi-context aware rating of the image. In particular, systems described herein can generate a plurality of probability context scores for an image. Moreover, the disclosed systems can generate a plurality of context-specific scores for an image. Utilizing each of the probability context scores and each of the corresponding context-specific scores for an image, the disclosed systems can generate a multi-context aware rating for the image. Thereafter, the disclosed systems can select an image from the plurality of images with the highest multi-context aware rating for delivery to the user. The disclosed system can utilize one or more neural networks to both generate the probability context scores for an image and to generate the context-specific scores for an image.

公开(公告)号：US10521705B2

公开(公告)日：2019-12-31

申请号：US15812695

申请日：2017-11-14

Applicant: Adobe Inc.

Inventor： Xin Lu ,  Zejun Huang ,  Jen-Chan Jeff Chien

IPC: G06K9/72 ,  G06K9/62 ,  G06K9/00 ,  H04N1/21 ,  G06F16/532 ,  G06F16/583

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media that automatically select an image from a plurality of images based on the multi-context aware rating of the image. In particular, systems described herein can generate a plurality of probability context scores for an image. Moreover, the disclosed systems can generate a plurality of context-specific scores for an image. Utilizing each of the probability context scores and each of the corresponding context-specific scores for an image, the disclosed systems can generate a multi-context aware rating for the image. Thereafter, the disclosed systems can select an image from the plurality of images with the highest multi-context aware rating for delivery to the user. The disclosed system can utilize one or more neural networks to both generate the probability context scores for an image and to generate the context-specific scores for an image.