Convolutional neural network optimisation to enhance ESPI fringe visibility

J. M. Crespo, V. Moreno
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引用次数: 1

Abstract

The use of convolutional neuronal networks (CNN) for the treatment of interferometric fringes has been introduced in recent years. In this paper, we optimize and build a CNN model, based U-NET architecture, to maximize its performance processing electronic speckle interferometry fringes (ESPI).
卷积神经网络优化,提高ESPI条纹可见性
卷积神经网络(CNN)用于干涉条纹的处理近年来已被引入。本文对基于U-NET结构的CNN模型进行了优化和构建,以最大限度地提高其处理电子散斑干涉条纹(ESPI)的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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