公开(公告)号：US10860858B2

公开(公告)日：2020-12-08

申请号：US16009559

申请日：2018-06-15

Applicant: Adobe Inc.

Inventor： Viswanathan Swaminathan ,  Saayan Mitra ,  Somdeb Sarkhel ,  Qi Lou

IPC: G06K9/00 ,  G06K9/62

Abstract: The present disclosure relates to systems, methods, and computer readable media that utilize a trained multi-modal combination model for content and text-based evaluation and distribution of digital video content to client devices. For example, systems described herein include training and/or utilizing a combination of trained visual and text-based prediction models to determine predicted performance metrics for a digital video. The systems described herein can further utilize a multi-modal combination model to determine a combined performance metric that considers both visual and textual performance metrics of the digital video. The systems described herein can further select one or more digital videos for distribution to one or more client devices based on combined performance metrics associated with the digital videos.

公开(公告)号：US20190384981A1

公开(公告)日：2019-12-19

申请号：US16009559

申请日：2018-06-15

Applicant: Adobe Inc.

Inventor： Viswanathan Swaminathan ,  Saayan Mitra ,  Somdeb Sarkhel ,  Qi Lou

IPC: G06K9/00 ,  G06K9/62

Abstract: The present disclosure relates to systems, methods, and computer readable media that utilize a trained multi-modal combination model for content and text-based evaluation and distribution of digital video content to client devices. For example, systems described herein include training and/or utilizing a combination of trained visual and text-based prediction models to determine predicted performance metrics for a digital video. The systems described herein can further utilize a multi-modal combination model to determine a combined performance metric that considers both visual and textual performance metrics of the digital video. The systems described herein can further select one or more digital videos for distribution to one or more client devices based on combined performance metrics associated with the digital videos.