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Method and device for providing integrated feature map using ensemble of multiple outputs from convolutional neural network

机译:使用卷积神经网络的多个输出的集成提供集成特征图的方法和设备

摘要

A method for providing an integrated feature map by using an ensemble of a plurality of outputs from a convolutional neural network (CNN) is provided. The method includes steps of: a CNN device (a) receiving an input image and applying a plurality of modification functions to the input image to thereby generate a plurality of modified input images; (b) applying convolution operations to each of the modified input images to thereby obtain each of modified feature maps corresponding to each of the modified input images; (c) applying each of reverse transform functions, corresponding to each of the modification functions, to each of the corresponding modified feature maps, to thereby generate each of reverse transform feature maps corresponding to each of the modified feature maps; and (d) integrating at least part of the reverse transform feature maps to thereby obtain an integrated feature map.
机译:提供一种用于通过使用来自卷积神经网络(CNN)的多个输出的集合来提供集成特征图的方法。该方法包括以下步骤:CNN设备(a)接收输入图像并将多个修改功能应用于该输入图像,从而生成多个修改后的输入图像;以及(b)对每个修改后的输入图像进行卷积运算,从而获得与每个修改后的输入图像相对应的每个修改后的特征图; (c)将与每个修改功能相对应的每个反向变换功能应用于每个对应的修改特征图,从而生成与每个修改特征图相对应的每个反向变换特征图; (d)对至少一部分逆变换特征图进行积分以获得积分特征图。

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