PERFORMANCE OF NEURAL NETWORKS USING LEARNED SPECIALIZED TRANSFORMATION FUNCTIONS

    公开(公告)号:US20210042625A1

    公开(公告)日:2021-02-11

    申请号:US16534856

    申请日:2019-08-07

    Applicant: ADOBE INC.

    Abstract: Methods and systems are provided for facilitating the creation and utilization of a transformation function system capable of providing network agnostic performance improvement. The transformation function system receives a representation from a task neural network. The representation can be input into a composite function neural network of the transformation function system. A learned composite function can be generated using the composite function neural network. The composite function can be specifically constructed for the task neural network based on the input representation. The learned composite function can be applied to a feature embedding of the task neural network to transform the feature embedding. Transforming the feature embedding can optimize the output of the task neural network.

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