公开(公告)号：US20230401830A1

公开(公告)日：2023-12-14

申请号：US18237550

申请日：2023-08-24

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Jianzhong HE ,  Shuaijun CHEN ,  Xu JIA ,  Jianzhuang LIU

IPC: G06V10/774 ,  G06V10/56 ,  G06V10/26 ,  G06N3/045

CPC classification number: G06V10/7753 ,  G06V10/56 ,  G06V10/26 ,  G06N3/045

Abstract: This application provides a model training method in the artificial intelligence field. In a process of determining a loss used to update a model parameter, factors are comprehensively considered. Therefore, an obtained neural network has a strong generalization capability. The method in this application includes: obtaining a first source domain image associated with a target domain image and a second source domain image associated with the target domain image; obtaining a first prediction label of the first source domain image and a second prediction label of the second source domain image through a first to-be-trained model; obtaining a first loss based on the first prediction label and the second prediction label, where the first loss indicates a difference between the first prediction label and the second prediction label; and updating a parameter of the first to-be-trained model based on the first loss, to obtain a first neural network.