ADAPTIVE TEXT RECOGNITION
    1.
    发明公开

    公开(公告)号:US20230237816A1

    公开(公告)日:2023-07-27

    申请号:US17586724

    申请日:2022-01-27

    发明人: Zi Sian Wong Bo Li

    IPC分类号: G06V20/62 G06V20/58 G06N20/20

    摘要: Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for generating a prediction of at least a text and a particular type associated with an object are described in this specification. A first model output is generated by using a first machine learning model to process input data including one or more objects. The first model output identifies an existence of a particular object in the input data and specifies characteristics of the particular object. A type of the particular object is determined based on the specified characteristics. The type comprises a single-row type and a multi-row type. A single-row representation of the particular object is generated. A second model output is generated by processing the single-row representation. The second model output comprises a prediction of characters corresponding to the particular vehicle license plate.

    Adaptive text recognition
    2.
    发明授权

    公开(公告)号:US12046054B2

    公开(公告)日:2024-07-23

    申请号:US17586724

    申请日:2022-01-27

    发明人: Zi Sian Wong Bo Li

    摘要: Methods, systems, and apparatuses, including computer programs encoded on computer storage media, for generating a prediction of at least a text and a particular type associated with an object are described in this specification. A first model output is generated by using a first machine learning model to process input data including one or more objects. The first model output identifies an existence of a particular object in the input data and specifies characteristics of the particular object. A type of the particular object is determined based on the specified characteristics. The type comprises a single-row type and a multi-row type. A single-row representation of the particular object is generated. A second model output is generated by processing the single-row representation. The second model output comprises a prediction of characters corresponding to the particular vehicle license plate.