Electronic device and method for predicting and compensating for burn-in of display

    公开(公告)号:US11948484B2

    公开(公告)日:2024-04-02

    申请号:US18328202

    申请日:2023-06-02

    Abstract: An electronic device with a rollable display may include the operations of: obtaining global burn-in information and local burn-in information according to a designated sampling period; on the basis of the result of analyzing the global burn-in information, predicting whether burn-in will at least partially occur in the entire area of a display area; when burn-in is predicted to at least partially occur in a boundary area, generating a first compensation map including pieces of local compensation data calculated to correspond to m block areas of the boundary area, respectively; when burn-in is predicted to at least partially occur in an area remaining after excluding the boundary area from the entire area, generating a second compensation map including pieces of global compensation data calculated to correspond to n block areas of the entire area, respectively; and controlling the rollable display to display image data compensated on the basis of the first compensation map or the second compensation map.

    Method and apparatus with neural network data quantizing

    公开(公告)号:US12106219B2

    公开(公告)日:2024-10-01

    申请号:US15931362

    申请日:2020-05-13

    CPC classification number: G06N3/084 G06N3/04 G06N3/0495

    Abstract: A neural network data quantizing method includes: obtaining local quantization data by firstly quantizing, based on a local maximum value for each output channel of a current layer of a neural network, global recovery data obtained by recovering output data of an operation of the current layer based on a global maximum value corresponding to a previous layer of the neural network; storing the local quantization data in a memory to perform an operation of a next layer of the neural network; obtaining global quantization data by secondarily quantizing, based on a global maximum value corresponding to the current layer, local recovery data obtained by recovering the local quantization data based on the local maximum value for each output channel of the current layer; and providing the global quantization data as input data for the operation of the next layer.

    Method for calculating degree of degradation on basis of properties of image displayed on display and electronic device for implementing same

    公开(公告)号:US11443690B2

    公开(公告)日:2022-09-13

    申请号:US17266013

    申请日:2019-06-04

    Abstract: Disclosed is an electronic device comprising at least one sensor, a communication circuit, a display, and at least one processor operationally connected to the display, wherein the at least one processor is configured to: display, on the display, a watch screen including a fixed element displayed at a designated location on the display, a repetitive element displayed on the basis of at least a designated rule, and a changing element associated with information obtained through the at least one sensor or received through the communication circuit; generate first data on the basis of at least one of the designated rule or the shape of the repetitive element; generate second data based on at least one of the fixed element or the changing element, in response to the changing element changing from a first value to a second value; and generate first deterioration information on the basis of the first data, the second data, and the duration over which the changing element maintains the first value. Various other embodiments understood through the specification are also possible.

    METHOD AND APPARATUS WITH NEURAL NETWORK DATA QUANTIZING

    公开(公告)号:US20210110270A1

    公开(公告)日:2021-04-15

    申请号:US15931362

    申请日:2020-05-13

    Abstract: A neural network data quantizing method includes: obtaining local quantization data by firstly quantizing, based on a local maximum value for each output channel of a current layer of a neural network, global recovery data obtained by recovering output data of an operation of the current layer based on a global maximum value corresponding to a previous layer of the neural network; storing the local quantization data in a memory to perform an operation of a next layer of the neural network; obtaining global quantization data by secondarily quantizing, based on a global maximum value corresponding to the current layer, local recovery data obtained by recovering the local quantization data based on the local maximum value for each output channel of the current layer; and providing the global quantization data as input data for the operation of the next layer.

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