公开(公告)号：US20230164446A1

公开(公告)日：2023-05-25

申请号：US17885035

申请日：2022-08-10

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Shengyu WEI ,  Yuning DU ,  Cheng CUI ,  Ruoyu GUO ,  Shuilong DONG ,  Bin LU ,  Tingquan GAO ,  Qiwen LIU ,  Xiaoguang HU ,  Dianhai YU ,  Yanjun MA

IPC: H04N5/235 ,  G06T7/11 ,  G06T7/80 ,  G02F1/133

CPC classification number: H04N5/2353 ,  G06T7/11 ,  G06T7/80 ,  G02F1/13306 ,  G06T2207/20081

Abstract: An imaging exposure control method and apparatus, a device and a storage medium, which relate to the field of artificial intelligence technologies, such as machine learning technologies and intelligent imaging technologies, are disclosed. An implementation includes performing semantic segmentation on a preformed image to obtain semantic segmentation images of at least two semantic regions; estimating an exposure duration of each semantic region based on the semantic segmentation image and the preformed image; and controlling exposure of each semantic region during imaging based on the exposure duration of each semantic region.

公开(公告)号：US20220247626A1

公开(公告)日：2022-08-04

申请号：US17718149

申请日：2022-04-11

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Cheng CUI ,  Tingquan GAO ,  Shengyu WEI ,  Yuning DU ,  Ruoyu GUO ,  Bin LU ,  Ying ZHOU ,  Xueying LYU ,  Qiwen LIU ,  Xiaoguang HU ,  Dianhai YU ,  Yanjun MA

IPC: H04L41/0806 ,  H04L41/084 ,  H04L41/0894 ,  G06K9/62

Abstract: The present disclosure provides a method for generating a backbone network, an apparatus for generating a backbone network, a device, and a storage medium. The method includes: acquiring a set of a training image, a set of an inference image, and a set of an initial backbone network; training and inferring, for each initial backbone network in the set of the initial backbone network, the initial backbone network by using the set of the training image and the set of the inference image, to obtain an inference time and an inference accuracy of a trained backbone network in an inference process; determining a basic backbone network based on the inference time and the inference accuracy of the trained backbone network in the inference process; and obtaining a target backbone network based on the basic backbone network and a preset target network.