基于机器学习的数字图像土壤分析

2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC) Pub Date : 2021-07-01 DOI:10.1109/ICNISC54316.2021.00127

Quchao Cheng, Jiaojie Li, Guochao Shen, Qingmin Du

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引用次数: 0

摘要

本文建立了一种基于机器学习的数字图像土壤分析模型。根据HSV和图像前景的均值，采用MLP和SVM两种算法对同一土壤中的药物含量进行预测，验证了MLP网络和支持向量机对图像分析的准确性。图像检测药物含量可应用于土地管理，为土壤综合分析提供多方面的新思路和有效参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Digital Image Soil Analysis based on Machine Learning

In this paper, a digital image soil analysis model based on machine learning is established.According to the mean value of HSV and image foreground, two algorithms, MLP and SVM, were used to predict the drug content in the same soil, which proved the accuracy of image analysis by MLP network and support vector machine. Drug content detection by image can be applied to land management, which provides a new idea and effective reference for comprehensive soil analysis in many aspects.

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来源期刊

2021 7th Annual International Conference on Network and Information Systems for Computers (ICNISC)

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