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Classification of cotton oil in the semi-refining process using image processing techniques: Image processing for industrial applications

机译:使用图像处理技术在半精炼过程中对棉油进行分类:工业应用的图像处理

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This paper presents a steps model classification in the cotton oil semi-refining process by image processing. A simple system of efficient analysis was obtained, allowing its use on the factory floor, assisting in the process with respect to the assertiveness in the desired semi-refined state and its quality control. Two algorithms with different recognition patterns were analyzed: K-Nearest Neighbor and Quadratic Discriminant Analysis, with a validation strategy Leave-one-out and the neural network Extreme Learning Machine using K-fold validation technique. Both algorithms reached success rates of more than 90%, and the best result was obtained through the applied neural network, with more than 95% of accuracy.
机译:本文提出了一种通过图像处理技术在棉油半精炼过程中进行模型分类的步骤。获得了一个简单的有效分析系统,可以在工厂车间使用,有助于在所需的半精制状态下的自信性及其质量控制方面的过程。分析了两种具有不同识别模式的算法:K最近邻算法和二次判别分析,以及一种采用K折验证技术的验证策略“留一法”和神经网络极限学习机。两种算法的成功率均超过90%,并且通过应用的神经网络获得了最佳结果,准确率超过95%。

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