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首页> 外文期刊>Optics Communications: A Journal Devoted to the Rapid Publication of Short Contributions in the Field of Optics and Interaction of Light with Matter >Neural network based face recognition by using diffraction pattern sampling with a digital ring-wedge detector
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Neural network based face recognition by using diffraction pattern sampling with a digital ring-wedge detector

机译:通过使用数字环形楔检测器的衍射图样采样来基于神经网络的人脸识别

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摘要

Use of neural networks (NNs) and diffraction pattern sampling by a ring-wedge detector leads to easier and faster algorithms for pattern recognition. An estimation was made of the optimum dimensions of a digital ring-wedge detector for sampling Fourier transform of random matrices through simulation of digital ring-wedge detector. The modulus squared Fourier transforms of facial images were sampled by ring-wedge geometry, and used for training a neural net for multi-face recognition. Fourier spectral intensities obtained by simulation and experiment were both tested for training and generalization of the network which was studied as a function of learning rate and number of epochs. (C) 2002 Elsevier Science B.V. All rights reserved. [References: 13]
机译:环形楔形检测器使用神经网络(NNs)和衍射图案采样可导致更轻松,更快速的图案识别算法。通过数字环形楔形检测器的仿真,估计了用于采样随机矩阵的傅立叶变换的数字环形楔形检测器的最佳尺寸。通过环形楔形几何对面部图像的模平方傅里叶变换进行采样,并将其用于训练神经网络以进行多人脸识别。通过模拟和实验获得的傅立叶光谱强度都经过测试,以训练和推广网络,并根据学习率和时期数进行了研究。 (C)2002 Elsevier Science B.V.保留所有权利。 [参考:13]

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