Optimum Conditions for Construction of Training Set in Fringe Analysis with Multilayer Neural Network

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概要

• 論文の詳細を見る

• A method of automatically processing a deformed fringe pattern in fringe projection profilometry to profile a three-dimensional (3D) object with a multilayer neural network has been investigated by computer simulation. The optimum projection conditions for the fringe pattern and the determination conditions for a training set for a learning process of the neural network were proposed to apply the multilayer neural network effectively. It is shown that the learning time in the neural network is reduced and that the performance of the profilometry is improved by the proposed optimization.

• Published by the Japan Society of Applied Physics through the Institute of Pure and Applied Physicsの論文
• 2009-09-25

著者

• Ohno Takahiro

  Electronic Technology Department, Kinki Polytechnic College, Kishiwada, Osaka 596-0103, Japan

• Nakagawa Kiyoshi

  Graduate School of Engineering, Kagawa University, Takamatsu 761-0396, Japan

• Nakagawa Kiyoshi

  Graduate School of Engineering, Kagawa University, 2217-20 Hayashimachi, Takamatsu 761-0396, Japan

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