TEXT RECOGNITION METHOD, AND MODEL AND ELECTRONIC DEVICE

    公开(公告)号:US20240320428A1

    公开(公告)日:2024-09-26

    申请号:US18638457

    申请日:2024-04-17

    CPC classification number: G06F40/279 G06V30/1912 G06V30/19127 G06V30/1916

    Abstract: Provided in the present disclosure are a text recognition method, and a model and an electronic device, which are applied to a mode in which primary classification is first performed from different dimensions, and secondary classification is then performed, such that the meaning of text is analyzed from different dimensions, thereby improving the accuracy of text recognition. The method includes: acquiring text to be recognized, and performing primary classification on the text to obtain a plurality of text features, wherein the primary classification is used for performing feature extraction on the text from different dimensions, and there are differences between features extracted from the different dimensions (100); splicing the plurality of text features, so as to obtain spliced features (101); and performing secondary classification on the spliced features to obtain a text category corresponding to the text, wherein the secondary classification is used for classifying the spliced features (102).

    TRAINING METHOD AND APPARATUS FOR MACHINE LEARNING MODEL, IMAGE PROCESSING METHOD AND APPARATUS

    公开(公告)号:US20240289960A1

    公开(公告)日:2024-08-29

    申请号:US18042700

    申请日:2022-02-28

    Inventor: Chuqian ZHONG

    CPC classification number: G06T7/11 G06N3/0464 G06T2207/20081

    Abstract: The present disclosure relates to a training method and training apparatus for a machine learning model, and a method and apparatus for image processing, which relates to the technical field of image processing. The training method for a machine learning model includes: expanding at least one pixel of an image sample to be processed into a pixel block, which comprises a plurality of pixels to be predicted; processing the pixel block using a first mask and obtain a mask processed result; according to the mask processed result, predicting prediction pixel values of the plurality of pixels to be predicted using a machine learning model; training a machine learning model according to the prediction pixel values of the plurality of pixels to be predicted and labeled pixel values of the plurality of pixels to be predicted.

    REGISTRATION SYSTEM
    8.
    发明申请

    公开(公告)号:US20220137733A1

    公开(公告)日:2022-05-05

    申请号:US17513713

    申请日:2021-10-28

    Abstract: A registration system is provided. The registration system includes: a display device, a collection device and an ultrasonic generating device. The display device is configured to display a graphical user interface. The collection device is configured to collect a scene image at the display device to recognize an operation of a user on the graphical user interface. The ultrasonic generating device is configured to emit ultrasonic signals, so that the ultrasonic signals gather to form one or more virtual buttons for operating the graphical user interface.

    OBJECT OPERATING METHOD AND APPARATUS, COMPUTER DEVICE, AND COMPUTER STORAGE MEDIUM

    公开(公告)号:US20250005356A1

    公开(公告)日:2025-01-02

    申请号:US18707804

    申请日:2023-07-31

    Abstract: Provided is an object operating method, includes: acquiring an object to be operated; inputting the object to be operated into a target model, wherein the target model is a trained neural network model and at least one set of parameters in the target model is acquired in a predetermined manner, and the target model is configured to carry out a recognition operation or a processing operation on the object to be operated; and acquiring an operation result output by the target model; wherein the predetermined manner includes: acquiring a collection of sample parameters corresponding to a first set of parameters of the target model, performing a plurality of iteration processing on the collection of sample parameters; acquiring a target set of parameters based on the collection of sample parameters subjected to the plurality of iteration processing; and determining the target set of parameters as the first set of parameters.

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