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    Method and apparatus for predicting passenger flow
    1.
    发明授权
    Method and apparatus for predicting passenger flow 有权

    公开(公告)号：US11526748B2

    公开(公告)日：2022-12-13

    申请号：US16455449

    申请日：2019-06-27

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

    Inventor： Yaobo Huang ,  Minghao Liu ,  Siyu An ,  Jiangliang Guo

    IPC: G06N3/08 ,  G06K9/62

    Abstract: Embodiments of the present disclosure disclose a method and apparatus for predicting a passenger flow. A specific implementation of the method includes: acquiring, based on a received prediction request for a passenger flow value of a target traffic route in a preset time period, route information of the target traffic route and a passenger flow sequence corresponding to a preset number of consecutive time periods before a current time; encoding the route information to generate encoded route information; and inputting the encoded route information and the passenger flow sequence into a pre-trained passenger flow prediction model to obtain a passenger flow prediction value of the target traffic route in the preset time period, the passenger flow prediction model being used to represent a corresponding relationship between both the encoded route information and the passenger flow sequence and the passenger flow prediction value of the target traffic route.

    Method and apparatus for inspecting burrs of electrode slice
    2.
    发明授权
    Method and apparatus for inspecting burrs of electrode slice 有权

    公开(公告)号：US11461995B2

    公开(公告)日：2022-10-04

    申请号：US16683766

    申请日：2019-11-14

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

    Inventor： Yawei Wen ,  Jiabing Leng ,  Minghao Liu ,  Jiangliang Guo ,  Xu Li

    IPC: G06V10/44 ,  G06K9/62

    Abstract: Embodiments of the present disclosure provides a method and apparatus for inspecting burrs of an electrode slice. The method may include: acquiring a to-be-inspected electrode slice image; and inputting the to-be-inspected electrode slice image into a pre-trained burr instance segmentation model to obtain inspection result for characterizing whether the electrode slice displayed in the to-be-inspected electrode slice image has burrs and contour of the burrs, where the burr instance segmentation model is used to characterize the corresponding relationship between the electrode slice image and the inspection result and contour information. The method may further include: and outputting, in response to the inspection result for characterizing that the electrode slice displayed in the to-be-inspected electrode slice image has burrs, prompt information for characterizing that the electrode slice displayed in the to-be-inspected electrode slice image has burrs.

    MODEL TRAINING METHOD, SHORT MESSAGE AUDITING MODEL TRAINING METHOD, SHORT MESSAGE AUDITING METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM
    7.
    发明公开
    MODEL TRAINING METHOD, SHORT MESSAGE AUDITING MODEL TRAINING METHOD, SHORT MESSAGE AUDITING METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM 审中-公开

    公开(公告)号：US20230351241A1

    公开(公告)日：2023-11-02

    申请号：US17639653

    申请日：2021-04-12

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

    Inventor： Huihui He ,  Leyi Wang ,  Minghao Liu ,  Jiangliang Guo

    IPC: G06N20/00 ,  G06N7/01

    CPC classification number: G06N20/00 ,  G06N7/01

    Abstract: The present application discloses a model training method, a short message auditing method and apparatuses, a device, and a storage medium, and relates to the field of artificial intelligence. A specific implementation solution of model training is: performing a sample reduction on first unlabeled samples to obtain second unlabeled samples; inputting the second unlabeled samples to a machine learning model for prediction, to obtain a probability corresponding to a result of predicting the second unlabeled samples; selecting a third unlabeled sample from the second unlabeled samples according to the probability; and training the machine learning model by using a third unlabeled sample after labeling. In embodiments of the present application, redundant samples are removed through a sample reduction, such that the selected samples have a certain degree of representativeness. In addition, a machine learning model is used to further select an informative sample with the most labeling significance for the current model by using an active learning technology, the cost of labeling is reduced.

    Battery detection method and device
    8.
    发明授权
    Battery detection method and device 有权

    公开(公告)号：US11158044B2

    公开(公告)日：2021-10-26

    申请号：US16650279

    申请日：2019-06-27

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

    Inventor： Yawei Wen ,  Jiabing Leng ,  Minghao Liu ,  Huihui Xiao ,  Jiangliang Guo ,  Xu Li

    IPC: G06T7/00

    Abstract: The present disclosure provides a battery detection method and a battery detection device. The method includes: obtaining a picture of each battery on a battery production line, and obtaining a corresponding production node; inputting the picture into a preset defect detection model, and obtaining a detection result output by the defect detection model, and when the detection result denotes that there is the defect on the picture, sending a control instruction to a control device of the production node corresponding to the picture, to cause the control device to shunt the battery corresponding to the picture having the defect based on the control instruction. The detection result includes whether there is a defect, a defect type, and a defect position.

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