首页> 外国专利> METHOD FOR RECOGNIZING FACE USING MULTIPLE PATCH COMBINATION BASED ON DEEP NEURAL NETWORK WITH FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATION

METHOD FOR RECOGNIZING FACE USING MULTIPLE PATCH COMBINATION BASED ON DEEP NEURAL NETWORK WITH FAULT TOLERANCE AND FLUCTUATION ROBUSTNESS IN EXTREME SITUATION

机译:基于深度故障容差和波动稳健性的深度神经网络的多补丁组合识别方法

摘要

A method for face recognition by using a multiple patch combination based on a deep neural network is provided. The method includes steps of: a face-recognizing device, (a) if a face image with a 1-st size is acquired, inputting the face image into a feature extraction network, to allow the feature extraction network to generate a feature map by applying convolution operation to the face image with the 1-st size, and to generate multiple features by applying sliding-pooling operation to the feature map, wherein the feature extraction network has been learned to extract a feature using a face image for training having a 2-nd size and wherein the 2-nd size is smaller than the 1-st size; and (b) inputting the multiple features into a learned neural aggregation network, to allow the neural aggregation network to aggregate the multiple features and to output an optimal feature for the face recognition.
机译:提供了一种基于深度神经网络的多补丁组合人脸识别方法。该方法包括以下步骤:面部识别装置,(a)如果获取具有第一尺寸的面部图像,则将该面部图像输入到特征提取网络中,以允许特征提取网络通过以下方式生成特征图:将卷积运算应用于具有第一大小的面部图像,并通过对特征图应用滑动合并运算来生成多个特征,其中,已经学习了特征提取网络以使用面部图像来提取特征,以用于训练具有第二尺寸,其中第二尺寸小于第一尺寸; (b)将多个特征输入到学习的神经聚合网络中,以允许神经聚合网络聚合多个特征并输出用于面部识别的最佳特征。

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