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METHOD AND DEVICE FOR PROVIDING INTEGRATED FEATURE MAP USING ENSEMBLE OF MULTIPLE OUTPUTS FROM CONVOLUTIONAL NEURAL NETWORK

机译:使用来自卷积神经网络的多个输出集成的集成特征映射的方法和装置

摘要

The present invention relates to a method and apparatus for providing a unified feature map using an ensemble of a plurality of outputs from a convolutional neural network. More specifically, the method comprising: (a) generating, by a CNN device, a plurality of transformed input images by receiving an input image, and applying a plurality of transform functions for transforming the input image; (b) obtaining, by the CNN device, each of the transformed feature maps corresponding to each of the transformed input images by applying a convolution operation to each of the transformed input images; (c) generating, by the CNN apparatus, an inverse transform function corresponding to each of the transform functions to each of the transformed feature maps to generate each inverse transform feature map corresponding to each of the transformed feature maps; and (d) obtaining, by the CNN apparatus, an integrated feature map by integrating at least some of the inverse transform feature maps.
机译:本发明涉及一种用于使用来自卷积神经网络的多个输出的集合提供统一特征映射的方法和装置。 更具体地,该方法包括:(a)通过CNN设备通过接收输入图像来产生多个变换的输入图像,并应用用于转换输入图像的多个变换功能; (b)通过CNN设备获得通过向每个变换的输入图像应用卷积操作对应于每个变换的输入图像的每个变换特征映射; (c)通过CNN装置生成与每个变换功能对应于每个变换的特征映射的逆变换功能以生成与每个变换的特征映射相对应的每个逆变换特征图; (d)通过CNN装置获得集成特征映射,通过集成至少一些逆变换特征映射。

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