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An intelligent model for detecting and classifying color-textured fabric defects using genetic algorithms and the elman neural network

机译:使用遗传算法和Elman神经网络的彩色织物疵点检测和分类智能模型

摘要

In this paper, an intelligent color-textured fabric defect detection and classification model using genetic algorithms and the Elman neural network is introduced. A color ring projection is used for image processing, and the solution for optimization of parameters is based on the genetic algorithm method. The new modified Elman network is proposed to classify the type of fabric defects, which have proportional, integral, and derivative properties. The proposed inspecting model in this study is more feasible and applicable in fabric and stitching garment defect detection and classification.
机译:本文提出了一种基于遗传算法和Elman神经网络的智能化彩色织物疵点检测与分类模型。彩色环形投影用于图像处理,参数优化的解决方案基于遗传算法。提出了新的改进的Elman网络,以对具有缺陷,比例和积分和导数性质的织物缺陷类型进行分类。本研究提出的检验模型在织物和缝制服装的缺陷检测和分类中更为可行和适用。

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