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Selecting suitable deep learning network for face recognition

机译:选择适合的人脸识别网络

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摘要

In this paper is given problems in face recognition methods and algorithms, ways of improving of recognition accuracy and decreasing errors. There are false acceptance and rejection errors in face recognition and these errors are decreased by normalization method when detected occlusion faces. For increasing face recognition accuracy and speed is proposed combining of deep learning networks and optimization of filter size.
机译:本文在面部识别方法和算法中给出了问题,提高了识别准确性和误差的方式。面部识别存在错误的接受和拒绝误差,并且当检测到遮挡面时,通过归一化方法减少这些误差。为了提高面部识别准确性和速度,提出了深度学习网络的组合和过滤尺寸的优化。

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