公开(公告)号：US20220319154A1

公开(公告)日：2022-10-06

申请号：US17843310

申请日：2022-06-17

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xinyu ZHANG ,  Peng YUAN ,  Muyuan FANG ,  Zhao ZHONG

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

Abstract: This application discloses a neural network model update method, an image processing method, and an apparatus in the field of artificial intelligence. The neural network model update method includes: obtaining a structure of a neural network model and a related parameter of the neural network model; training the neural network model based on the related parameter of the neural network model to obtain a trained neural network model; and if an evaluation result of the trained neural network model does not meet a preset condition, updating at least two items of the related parameter of the neural network model and the structure of the neural network model until an evaluation result of an updated neural network model meets a preset condition and/or a quantity of updates reaches a preset quantity of times. According to the method in this application, efficiency of updating a neural network model can be improved.

公开(公告)号：US20220215259A1

公开(公告)日：2022-07-07

申请号：US17701101

申请日：2022-03-22

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xinyu ZHANG ,  Peng YUAN ,  Zhao ZHONG

IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62

Abstract: Technical solutions in this application are applied to the field of artificial intelligence. This application provides a neural network training method, a method for performing data processing by using a neural network trained by using the method, and a related apparatus. According to the training method in this application, a target neural network is trained in an adversarial manner, so that a policy search module can continuously discover a weakness of the target neural network, generate a policy of higher quality according to the weakness, and perform data augmentation according to the policy to obtain data of higher quality. A target neural network of higher quality can be trained according to the data. In the data processing method in this application, data processing is performed by using the foregoing target neural network, so that a more accurate processing result can be obtained.

公开(公告)号：US20210342170A1

公开(公告)日：2021-11-04

申请号：US17376305

申请日：2021-07-15

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Jianbang WU ,  Peng YUAN

IPC: G06F9/455 ,  H04L29/08 ,  H04L12/24

Abstract: Embodiments of the present application provide an acceleration management node. The acceleration management node separately receives acceleration device information of all acceleration devices. The acceleration device information includes an algorithm type, an acceleration bandwidth or non-uniform memory access architecture (NUMA). The acceleration management node obtains an invocation request from a client. The acceleration management node queries the acceleration device information to determine, from all the acceleration devices of the at least one acceleration node, a target acceleration device matching the invocation request. The acceleration management node further instructs a target acceleration node to respond to the invocation request.