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Analyzing the Accuracy of KNN-based Cacao Bean Grading System

机译:基于KNN的神科豆分级系统的准确性分析

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摘要

Cacao is one of the major crops of the tropical world and is known worldwide for its beans used for manufacturing of products which are highly popular and widely consumed around the world such as chocolate and cocoa powder. Grading the cacao beans is a method utilized by the cacao experts and farmers to ensure valuable and good supply of cacao beans in the market. However, manual grading of the cacao beans using the naked eye observation is more laborious, time consuming and less accurate. To automate the said process, a computer-based cacao beans grading system was developed using image processing and KNN algorithm. One hundred ninety (190) samples were consumed as training examples and sixty samples (60) for classification. The system was designed and developed using C# Windows Form Application as its programming language, XAMPP as its server scripting language, and MySQL as its database. The accuracy calculation of the system resulted to 93.33%, which implies that the KNN model was able to effectively grade cacao beans.
机译:Cacao是热带世界的主要作物之一,在全球范围内为其豆类而着名,用于制造产品,这些产品非常受欢迎,广泛消耗巧克力和可可粉等世界。可可豆的评分是可可专家和农民使用的方法,以确保市场上的可粘糊豆提供有价值和良好的供应。然而,使用肉眼观察的可可豆的手动分级更加费力,耗时和更低的准确性。为了自动化所述过程,使用图像处理和KNN算法开发了一种基于计算机的恶豆分级系统。一百九十(190)个样品被消耗作为训练例和六十个样品(60)进行分类。使用C#Windows表单应用程序作为其编程语言,XAMPP作为其服务器脚本语言以及MySQL作为其数据库的数据库设计和开发。系统的精度计算导致93.33%,这意味着KNN模型能够有效地等级可可豆。

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