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An analysis of the performance of Artificial Neural Network technique for apple classification

机译:人工神经网络技术在苹果分类中的性能分析

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The purpose of this paper is to develop Artificial Neural Network (ANN)-based apple classifier. Testing effort is calculated using ANN method. The complete system is divided into two modules. In the first module, input (surface level apple quality parameter) from the different sources is collected by the software developed in Visual Basic through different input device like web camera, weight machine, etc. In the second module, the input data are used by ANN simulator to classify the apple according to their quality. The final result of an ANN model for apple classification is discussed; however, the modeling results showed that there is excellent agreement between the experimental data and predicted values. A low level of error prediction confirmed the fact that the Neural Network model is an effective instrument of the apple quality estimation. There is not any misclassification during testing. The paper presents alternative method for quality assessment of apple and provides consumers with a safer food supply.
机译:本文的目的是开发基于人工神经网络(ANN)的苹果分类器。测试工作量是使用ANN方法计算的。完整的系统分为两个模块。在第一个模块中,由Visual Basic开发的软件通过不同的输入设备(例如网络摄像头,称重机等)收集来自不同来源的输入(表面水平的苹果质量参数)。在第二个模块中,输入数据由ANN模拟器根据其质量对苹果进行分类。讨论了用于苹果分类的ANN模型的最终结果;然而,建模结果表明,实验数据与预测值之间具有极好的一致性。低水平的错误预测确认了以下事实:神经网络模型是苹果品质评估的有效工具。在测试过程中没有任何错误分类。本文提出了苹果质量评估的替代方法,并为消费者提供了更安全的食品供应。

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