公开(公告)号：US20210012198A1

公开(公告)日：2021-01-14

申请号：US17033316

申请日：2020-09-25

Applicant: Huawei Technologies Co., Ltd. ,  The University of Sydney

Inventor： Weichen ZHANG ,  Wanli OUYANG ,  Dong XU ,  Wen LI ,  Xiaofei WU ,  Jianzhuang LIU ,  Li QIAN

IPC: G06N3/08 ,  G06K9/62 ,  G06N3/04

Abstract: The present disclosure relates to artificial intelligence, and proposes a cooperative adversarial network. A loss function is set at a lower layer of the cooperative adversarial network, and is used to learn a domain discriminating feature. In addition, a cooperative adversarial target function includes the loss function and a domain invariant loss function that is set at a last layer (that is, a higher layer) of the cooperative adversarial network, to learn both the domain discriminating feature and a domain-invariant feature. Further, an enhanced collaborative adversarial network is proposed. Based on the collaborative adversarial network, target domain data is added to training of the collaborative adversarial network, an adaptive threshold is set based on precision of a task model, to select a target domain training sample, network confidence is discriminated based on a domain, and a weight of the target domain training sample is set.