公开(公告)号：US20210365738A1

公开(公告)日：2021-11-25

申请号：US17444427

申请日：2021-08-04

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

Inventor： Zhuang Jia ,  Xiang Long ,  Honghui Zheng ,  Yan Peng ,  Yuan Feng ,  Bin Zhang ,  Xiaodi Wang ,  Pengcheng Yuan ,  Ying Xin ,  Shumin Han

IPC: G06K9/62 ,  G06K9/00

Abstract: The present disclosure discloses a method and apparatus for training a model, a method and apparatus for predicting a mineral, a device and a storage medium, and relates to the fields of computer vision and deep learning technologies. An implementation of the method may include: acquiring a target hyperspectral image of a target area, the target hyperspectral image including at least one pixel point annotated with a mineral category; determining a mask image corresponding to the target hyperspectral image; determining a sample hyperspectral image according to the target hyperspectral image and the mask image; determining an annotation vector of each pixel point according to the at least one pixel point annotated with the mineral category; and training a model according to the sample hyperspectral image and the annotation vector of the each pixel point.

公开(公告)号：US11568347B2

公开(公告)日：2023-01-31

申请号：US17126826

申请日：2020-12-18

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

Inventor： Zhuang Jia ,  Hanchenxi Xu ,  Haocheng Liu ,  Yuan Li ,  Lingpeng Fang

IPC: G06Q10/06 ,  G06F40/20 ,  G06N7/00

Abstract: A method and apparatus for processing risk-management feature factors based on user generated content (UGC), an electronic device and a storage medium are disclosed, which relates to the fields of artificial intelligence and cloud computing. An implementation includes generating a feature expression of the UGC based on the UGC; and extracting the risk-management feature factors of the UGC according to a pre-generated risk-management-feature-factor extracting model and the feature expression of the UGC. According to the technology of the present application, the risk-management feature factors of a corresponding user may be extracted based on the UGC without depending on privacy information of the user, such as personal basic attributes, or the like, such that subsequent related processing actions of risk management may be facilitated, an acquiring way and an acquiring mode of the risk-management feature factors may be enriched effectively, and richer information of the risk-management feature factors may be acquired.

公开(公告)号：US11669990B2

公开(公告)日：2023-06-06

申请号：US17412574

申请日：2021-08-26

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

Inventor： Yan Peng ,  Xiang Long ,  Shumin Han ,  Honghui Zheng ,  Zhuang Jia ,  Xiaodi Wang ,  Pengcheng Yuan ,  Yuan Feng ,  Bin Zhang ,  Ying Xin

IPC: G06T7/62 ,  G06F18/241 ,  G06F18/25 ,  G06F18/2137 ,  G06V10/764 ,  G06V10/80 ,  G06V10/82 ,  G06V10/32 ,  G06V10/50 ,  G06V10/26 ,  G06V20/13

CPC classification number: G06T7/62 ,  G06F18/2137 ,  G06F18/241 ,  G06F18/253 ,  G06V10/26 ,  G06V10/32 ,  G06V10/50 ,  G06V10/764 ,  G06V10/809 ,  G06V10/82 ,  G06V20/13 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: An object area measurement method and an apparatus are provided, relating to the computer vision and deep learning technology. The method includes acquiring an original image with a spatial resolution, the original image including a target object; acquiring an object identification model including at least two sets of classification models; generating one or more original image blocks based on the original image; performing operations on each original image block: scaling each original image block at at least two scaling levels to obtain scaled image blocks with at least two sizes, the scaled image blocks respectively corresponding to the at least two sets of classification models, and inputting the scaled image blocks into the object identification model to obtain an identification result of the target object; and determining an area of the target object based on the respective identification results of the one or more original image blocks and the spatial resolution.

公开(公告)号：US20210390728A1

公开(公告)日：2021-12-16

申请号：US17412574

申请日：2021-08-26

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

Inventor： Yan PENG ,  Xiang Long ,  Shumin Han ,  Honghui Zheng ,  Zhuang Jia ,  Xiaodi Wang ,  Pengcheng Yuan ,  Yuan Feng ,  Bin Zhang ,  Ying Xin

IPC: G06T7/62 ,  G06K9/32 ,  G06K9/52 ,  G06K9/62

Abstract: An object area measurement method and an apparatus are provided, relating to the computer vision and deep learning technology. The method includes acquiring an original image with a spatial resolution, the original image including a target object; acquiring an object identification model including at least two sets of classification models; generating one or more original image blocks based on the original image; performing operations on each original image block: scaling each original image block at at least two scaling levels to obtain scaled image blocks with at least two sizes, the scaled image blocks respectively corresponding to the at least two sets of classification models, and inputting the scaled image blocks into the object identification model to obtain an identification result of the target object; and determining an area of the target object based on the respective identification results of the one or more original image blocks and the spatial resolution.