METHOD AND DEVICE WITH NEURAL NETWORK
    19.
    发明公开

    公开(公告)号:US20230252283A1

    公开(公告)日:2023-08-10

    申请号:US17982618

    申请日:2022-11-08

    CPC classification number: G06N3/08

    Abstract: A processor-implemented method with a neural network includes: generating a first intermediate vector by applying a first activation function to first nodes in a first intermediate layer adjacent to an input layer among intermediate layers of the neural network; transferring the first intermediate vector to second nodes in a second intermediate layer adjacent to an output layer among the intermediate layers; generating a second intermediate vector by applying a second activation function to the second nodes; and applying the second intermediate vector to an output layer of the neural network, wherein the second activation function is determined by a first hyperparameter of which a multiplier of the second activation function is associated with an ascending slope of the second activation function and a second hyperparameter of which the multiplier is associated with a descending slope of the second activation function to fix a peak value of the second activation function.

    METHOD AND APPARATUS WITH BIOMETRIC SPOOFING CONSIDERATION

    公开(公告)号:US20220319238A1

    公开(公告)日:2022-10-06

    申请号:US17670028

    申请日:2022-02-11

    Abstract: A method and apparatus with spoofing consideration is provided. The method includes implementing convolution block(s) of a machine learning model that determines whether biometric information in an input image is spoofed, including generating a feature map including channels for an input feature map for the input image using convolution layers of a convolution block of the convolution block(s), in response to a total number of input channels of the convolution block and a total number of output channels of the convolution block being different, matching the total number of input channels of the convolution block and the total number of output channels of the convolution block by adding a zero-padding channel to the input feature map using a skip connection structure, and generating output data for determining whether the biometric information is spoofed, dependent on the generated feature map and a result of the skip connection structure.

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