METHOD AND APPARATUS WITH TEACHERLESS STUDENT MODEL FOR CLASSIFICATION

    公开(公告)号:US20240242082A1

    公开(公告)日:2024-07-18

    申请号:US18338732

    申请日:2023-06-21

    CPC classification number: G06N3/09 G06N3/048

    Abstract: An apparatus and method for training a neural network model for classification without a teacher model are disclosed. The includes: selecting classes from a database comprising a set of classes; generating a mean feature group comprising mean features extracted from the selected classes; receiving a batch comprising input data and extracting, by the neural network model, a feature from the input data, wherein the neural network model is to be trained according to a mean feature set; determining a first similarity between the extracted feature and a mean feature corresponding to the input data; determining a second similarity comprising a self-similarity of the mean feature; and updating a parameter of the neural network model based on the first similarity and the second similarity.

    DEVICE AND METHOD WITH OBJECT RECOGNITION
    8.
    发明公开

    公开(公告)号:US20230283876A1

    公开(公告)日:2023-09-07

    申请号:US17958564

    申请日:2022-10-03

    CPC classification number: H04N5/23218 H04N5/23299 H04N5/23296

    Abstract: A device and method with object recognition is included. In one general aspect, an electronic device includes a camera sensor configured to capture a first image of a scene, the camera sensor is configured to perform at least one type of physical camera motion relative to the electronic device, the at least one type of physical camera motion includes rolling, panning, tilting, or zooming the camera sensor relative to the electronic device, and a processor configured to control the camera sensor to perform a physical motion of the physical camera motion type based on detecting an object in the first image, acquire a second image captured using the camera sensor as adjusted based on the performed physical motion, and recognize the object in the second image.

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