Adaptive Search Method and Apparatus for Neural Network

    公开(公告)号:US20220351019A1

    公开(公告)日:2022-11-03

    申请号:US17864521

    申请日:2022-07-14

    Abstract: An adaptive search method includes: receiving a search condition set comprising target hardware platform information, network structure information of a source neural network, and one or more evaluation metrics; performing a training process on a to-be-trained super network based on a training dataset to obtain a trained super network, by extending a network structure of the source neural network; and performing a subnet search process on the trained super network based on the one or more evaluation metrics to obtain network structure information of a target neural network, which represents the target neural network and an evaluation result of the target neural network running on a target hardware platform is better than an evaluation result of the source neural network running on the target hardware platform.

    FACE SEARCH METHOD AND APPARATUS
    2.
    发明申请

    公开(公告)号:US20220165091A1

    公开(公告)日:2022-05-26

    申请号:US17671253

    申请日:2022-02-14

    Abstract: A face search method and apparatus are provided. The method includes obtaining a to-be-searched face image, and inputting the face image into a first feature extraction model to obtain a first face feature. The method further includes inputting the face image and the first face feature into a first feature mapping model for feature mapping, to output a standard feature corresponding to the first face feature, and performing face search for the face image based on the standard feature. Features extracted by using a plurality of feature extraction models are concatenated, and a concatenated feature is used as a basis for constructing a standard feature.

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